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ICCV2019最新录用情况

本内容现在是ICCV2019,后期会更新为ICCV2021以随时更新

Awesome-ICCV2019 更新所有录用论文（已更新1000余篇ICCV2019论文）

Last updated: 2021/01/25

【计算机视觉联盟】回复【ICCV2019】即可获得百度云所有论文下载链接

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Update log

  • 2019/07/26 * - 更新28篇IIAI录用论文
  • 2019/07/28 * - 更新11篇旷视ICCV2019
  • 2019/08/28 * - 更新31篇Oral
  • 2019/08/29 * - 增加116篇ICCV2019文章
  • 2019/08/29 * - 增加35篇包含开源代码的ICCV2019
  • 2019/09/12 * - ICCV 1998-2017最佳论文
  • 2019/10/26 * - ICCV 所有论文百度云链接更新

Table of Contents

ICCV 简介

ICCV 的全称是 IEEE International Conference on Computer Vision，即国际计算机视觉大会，由IEEE主办，与计算机视觉模式识别会议（CVPR）和欧洲计算机视觉会议（ECCV）并称计算机视觉方向的三大顶级会议，被澳大利亚ICT学术会议排名和中国计算机学会等机构评为最高级别学术会议，在业内具有极高的评价。 不同于在美国每年召开一次的CVPR和只在欧洲召开的ECCV，ICCV在世界范围内每两年召开一次。ICCV论文录用率非常低，是三大会议中公认级别最高的 。上一届提交的论文中，其中621篇被接收，录用比例达 28.9%；其中 poster、spotlight、oral 的比例分别为 24.61%、2.61% 以及 2.09%。

ICCV主席

今年有一名大会主席是来自香港中文大学的信息工程系系主任汤晓鸥，他同时还是中国科学院深圳先进技术研究院的副院长兼商汤科技创始人。其他三名大会主席则分别是首尔大学的 Kyoung Mu Lee 教授、伊利诺伊大学厄巴纳-香槟分校的 David Forsyth 教授以及苏黎世联邦理工学院的 Marc Pollefeys 教授。

召开地点

本届大会最终的递交补充材料的截止日期为 3 月 29 日。大会召开时间为2019年10月27日至11月2日，举行地点是韩国首尔的 COEX 会议中心。

刚刚，计算机视觉三大顶会之一ICCV2019终于公布了它的最终论文接收结果，一共有1077篇论文被接收，接收率为25.02%

ICCV2019最新录用论文编号：

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起源人工智能研究院 - Inception Institute of Artificial Intelligence (IIAI) 28篇论文

IIAI主页：www.inceptioniai.org/

  1. Unsupervised Video Object Segmentation via Attentive Graph Neural Networks

  2. DUAL-GLOWs: Conditional Flow-Based Generative Models for Inter-Modality Transfer in Brain Imaging

  3. Unsupervised Graph Association for Person Re-identification

  4. Relational Attention Network for Crowd Counting

  5. Attentional Neural Fields for Crowd Counting

  6. Learning Compositional Neural Information Fusion for Human Parsing

  7. RANet: Ranking Attention Network for Fast Video Object Segmentation

  8. Learning to Mask Visible Regions for Occluded Pedestrian Detection

  9. Boosted Feature Guided Refinement Network for Single-Shot Detection

  10. Deep Contextual Attention for Human-Object Interaction Detection

  11. Learning the Model Update for Siamese Trackers

  12. 3C-Net: Category Count and Center Loss for Weakly-Supervised Action Localization

  13. Learning Rich Features at High-Speed for Single-Shot Object Detection

  14. Transductive learning for zero-shot object detection

  15. Ground-to-aerial Image Geo-localization with a Hard Exemplar Reweighting Triplet Loss

  16. Towards Bridging Semantic Gap to Improve Semantic Segmentation

  17. Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks

  18. Motion Deblurring via Human-Aware Attention Network

  19. Gaussian Affinity for Max-margin Class Imbalanced Learning

  20. A Deep Step Pattern Representation for Multimodal Retinal Image Registration

  21. SegEQA: Video Segmentation based Visual Attention for Embodied Question Answering

  22. Reciprocal Multi-Layer Subspace Learning for Multi-View Clustering

  23. Scoot: A Perceptual Metric for Facial Sketches

  24. EGNet: Edge Guidance Network for Salient Object Detection

  25. PointAE: Point Auto-encoder for 3D Statistical Shape and Texture Modelling

  26. Understanding Human Gaze Communication by Spatio-temporal Graph Reasoning

  27. Optimizing the F-measure for Threshold-free Salient Object Detection

  28. SynDeMo: Synergistic Deep Feature Alignment for Joint Learning of Depth and Ego-Motion

旷视研究院 11 篇论文入选 ICCV 2019

1、Objects365: A Large-scale, High-quality Dataset for Object Detection

2、ThunderNet: Towards Real-time Generic Object Detection

3、Efficient and Accurate Arbitrary-Shaped Text Detection with PixelAggregation Network

4、Semi-supervised Skin Detection by Network with Mutual Guidance

5、Semi-Supervised Video Salient Object Detection Using Pseudo-Labels

6、Disentangled Image Matting

7、Re-ID Driven Localization Refinement for Person Search

8、Vehicle Re-identification with Viewpoint-aware Metric Learning

9、MetaPruning: Meta Learning for Automatic Neural Network ChannelPruning

10、Symmetry-constrained Rectification Network for Scene Text Recognition

11、Learning to Paint with Model-based Deep Reinforcement Learning

2019 ICCV Oral

https://arxiv.org/abs/1908.00382
  1. Interpolated Convolutional Networks for 3D Point Cloud Understanding
https://arxiv.org/abs/1908.04512
  1. Memory-Based Neighbourhood Embedding for Visual Recognition
https://arxiv.org/abs/1908.04992
  1. Learning Trajectory Dependencies for Human Motion Prediction
https://arxiv.org/abs/1908.05436
  1. Domain Adaptation for Structured Output via Discriminative Patch Representations
https://arxiv.org/abs/1901.05427
  1. Deep Non-Rigid Structure from Motion
https://arxiv.org/abs/1908.00052
  1. Scalable Place Recognition Under Appearance Change for Autonomous Driving
https://arxiv.org/abs/1908.00178
  1. Restoration of Non-rigidly Distorted Underwater Images using a Combination of Compressive Sensing and Local Polynomial Image Representations
https://arxiv.org/abs/1908.01940
  1. Consensus Maximization Tree Search Revisited
https://arxiv.org/abs/1908.02021
  1. Weakly Supervised Energy-Based Learning for Action Segmentation
  2. Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification
https://arxiv.org/abs/1811.10144
  1. Controllable Artistic Text Style Transfer via Shape-Matching GAN
https://arxiv.org/abs/1905.01354
  1. Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition
https://arxiv.org/abs/1907.13369
  1. Expectation-Maximization Attention Networks for Semantic Segmentation
https://arxiv.org/abs/1907.13426
  1. VideoBERT: A Joint Model for Video and Language Representation Learning
https://arxiv.org/abs/1904.01766
  1. CARAFE: Content-Aware ReAssembly of FEatures
https://arxiv.org/pdf/1905.02188.pdf
  1. Habitat: A Platform for Embodied AI Research
https://arxiv.org/abs/1904.01201
  1. Equivariant Multi-View Networks
https://arxiv.org/abs/1904.00993
  1. PointFlow : 3D Point Cloud Generation with Continuous Normalizing Flows
https://arxiv.org/abs/1906.12320
  1. Learnable Triangulation of Human Pose
https://arxiv.org/abs/1905.05754
  1. Learning Implicit Generative Models by Matching Perceptual Features
https://arxiv.org/abs/1904.02762v1
  1. COCO-GAN: Generation by Parts via Conditional Coordinating
https://arxiv.org/abs/1904.00284
  1. SlowFast Networks for Video Recognition
https://arxiv.org/abs/1812.03982
  1. Exploring Randomly Wired Neural Networks for Image Recognition
https://arxiv.org/abs/1904.01569
  1. Can GCNs Go as Deep as CNNs?
https://arxiv.org/abs/1904.03751
  1. Deep SR-ITM: Joint Learning of Super-resolution and Inverse Tone-Mapping for 4K UHD HDR Applications
https://arxiv.org/abs/1904.11176
  1. Meta-Sim Learning to Generate Synthetic Datasets
https://arxiv.org/abs/1904.11621
  1. Deep HoughVoting for 3D Object Detection in Point Clouds
https://arxiv.org/abs/1904.09664
  1. Variational Adversarial Active Learning
https://arxiv.org/abs/1904.00370
  1. Towards Unconstrained End-to-End Text Spotting
https://arxiv.org/abs/1908.09231
  1. Non-local Recurrent Neural Memory for Supervised Sequence Modeling
https://arxiv.org/abs/1908.09535
  1. Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels
https://arxiv.org/abs/1908.09597

增加116篇ICCV2019文章

  1. Similarity-Preserving Knowledge Distillation
https://arxiv.org/abs/1907.09682
  1. GA-DAN: Geometry-Aware Domain Adaptation Network for Scene Text Detection and Recognition
https://arxiv.org/abs/1907.09653
  1. Tell, Draw, and Repeat: Generating and modifying images based on continual linguistic instruction
https://arxiv.org/pdf/1811.09845.pdf
  1. Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers
https://arxiv.org/abs/1904.08489
  1. nocaps: novel object captioning at scale
https://arxiv.org/abs/1812.08658
  1. ThunderNet: Towards Real-time Generic Object Detection
https://arxiv.org/abs/1903.11752
  1. Scene GraphPrediction with Limited Labels
https://arxiv.org/abs/1904.11622
  1. Ego-Pose Estimation and Forecasting as Real-Time PD Control
https://arxiv.org/abs/1906.03173
  1. The Trajectron: Probabilistic Multi-Agent Trajectory Modeling withDynamic Spatiotemporal Graphs
https://arxiv.org/abs/1810.05993
  1. End-to-End Learning of Representations for Asynchronous Event-BasedData
https://arxiv.org/abs/1904.08245
  1. Efficient Learning on Point Clouds with Basis Point Sets
https://arxiv.org/abs/1908.09186
  1. Dynamic Kernel Distillation for Efficient Pose Estimation in Videos
https://arxiv.org/abs/1908.09216
  1. Single-Stage Multi-Person Pose Machines
https://arxiv.org/abs/1908.09220
  1. Towards Unsupervised Image Captioning with Shared Multimodal Embeddings
https://arxiv.org/abs/1908.09317
  1. advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns
https://arxiv.org/abs/1908.09327
  1. Shape-Aware Human Pose and Shape Reconstruction Using Multi-View Images
https://arxiv.org/abs/1908.09464
  1. Relation Distillation Networks for Video Object Detection
https://arxiv.org/abs/1908.09511
  1. Object-Driven Multi-Layer Scene Decomposition From a Single Image
https://arxiv.org/abs/1908.09521
  1. Embarrassingly Simple Binary Representation Learning
https://arxiv.org/abs/1908.09573
  1. Moulding Humans: Non-parametric 3D Human Shape Estimation from Single Images
https://arxiv.org/abs/1908.00439
  1. Learning the Model Update for Siamese Trackers
https://arxiv.org/abs/1908.00855
  1. Distilling Knowledge From a Deep Pose Regressor Network
https://arxiv.org/abs/1908.00858
  1. Permutation-invariant Feature Restructuring for Correlation-aware Image Set-based Recognition
https://arxiv.org/abs/1908.01174
  1. ARGAN: Attentive Recurrent Generative Adversarial Network for Shadow Detection and Removal
https://arxiv.org/abs/1908.01323
  1. Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation
https://arxiv.org/abs/1908.01491
  1. View N-gram Network for 3D Object Retrieval
https://arxiv.org/abs/1908.01958
  1. Semi-supervised Skin Detection by Network with Mutual Guidance
https://arxiv.org/abs/1908.01977
  1. Deep Self-Learning From Noisy Labels
https://arxiv.org/abs/1908.02160
  1. Learning Aberrance Repressed Correlation Filters for Real-Time UAV Tracking
https://arxiv.org/abs/1908.02231
  1. Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning
https://arxiv.org/abs/1908.02441
  1. Expert Sample Consensus Applied to Camera Re-Localization
https://arxiv.org/abs/1908.02484
  1. SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition
https://arxiv.org/abs/1908.02660
  1. GP2C: Geometric Projection Parameter Consensus for Joint 3D Pose and Focal Length Estimation in the Wild
https://arxiv.org/abs/1908.02809
  1. SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
https://arxiv.org/abs/1904.01416
  1. Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction
https://arxiv.org/abs/1907.12704
  1. Orientation-aware Semantic Segmentation on Icosahedron Spheres
https://arxiv.org/abs/1907.12849
  1. EMPNet: Neural Localisation and Mapping using Embedded Memory Points
https://arxiv.org/abs/1907.13268
  1. SceneGraphNet: Neural Message Passing for 3D Indoor Scene Augmentation
https://arxiv.org/abs/1907.11308
  1. On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method
https://arxiv.org/abs/1907.11684
  1. Goal-Driven Sequential Data Abstraction
https://arxiv.org/abs/1907.12336
  1. Recursive Cascaded Networks for Unsupervised Medical Image Registration
https://arxiv.org/abs/1907.12353
  1. Learn to Scale: Generating Multipolar Normalized Density Map for Crowd Counting
https://arxiv.org/abs/1907.12428
  1. HoloGAN: Unsupervised learning of 3D representations from natural images
https://arxiv.org/abs/1904.01326
  1. MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning
https://arxiv.org/abs/1903.10258
  1. FrameNet: Learning Local Canonical Frames of 3D Surfaces from a Single RGB Image
https://arxiv.org/pdf/1903.12305.pdf
  1. Face De-occlusion using 3D Morphable Model and Generative Adversarialhttp://image.inha.ac.kr/paper/ICCV2019_Xaiowei.pdf
  2. Deep Meta Learning for Real-Time Target-Aware Visual Tracking
https://arxiv.org/pdf/1712.09153.pdf
  1. Switchable Whitening for Deep Representation Learning
https://arxiv.org/abs/1904.09739
  1. Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
https://arxiv.org/abs/1904.05049
  1. Multi-layer Depth and Epipolar Feature Transformers for 3D Scene Reconstruction
https://arxiv.org/abs/1902.06729
  1. Task2Vec: Task Embedding for Meta-Learning
https://arxiv.org/abs/1902.03545
  1. ACE: Adapting to Changing Environments for Semantic Segmentation
https://arxiv.org/pdf/1904.06268.pdf
  1. Few-shot Object Detection via Feature Reweighting
https://arxiv.org/pdf/1812.01866.pdf
  1. Disentangling Propagation and Generation for Video Prediction
https://arxiv.org/pdf/1812.00452.pdf
  1. An Empirical Study of Spatial Attention Mechanisms in Deep Networks
https://arxiv.org/pdf/1904.05873.pdf
  1. Fashion++: Minimal Edits for Outfit Improvement
https://arxiv.org/pdf/1904.09261.pdf
  1. Align2Ground: Weakly Supervised Phrase Grounding Guided by Image-Caption Alignment
https://arxiv.org/pdf/1903.11649.pdf
  1. Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded
https://arxiv.org/pdf/1902.03751.pdf
  1. SplitNet: Sim2Sim and Task2Task Transfer for Embodied Visual Navigation
https://arxiv.org/pdf/1905.07512.pdf
  1. EM-Fusion: Dynamic Object-Level SLAM with Probabilistic Data Association
https://arxiv.org/abs/1904.11781
  1. Texture Fields: Learning Texture Representations in Function Space
https://arxiv.org/abs/1905.07259
  1. AMASS: Archive of Motion Capture as Surface Shapes
https://arxiv.org/abs/1904.03278
  1. End-to-end Learning for Graph Decomposition
https://arxiv.org/pdf/1812.09737.pdf
  1. Towards Multi-pose Guided Virtual Try-on Network
https://arxiv.org/abs/1902.11026
  1. Learning to Reconstruct 3D Manhattan Wireframes from a Single Image
https://arxiv.org/abs/1905.07482
  1. Coherent Semantic Attention for Image Inpainting
https://arxiv.org/abs/1905.12384
  1. LayoutVAE: Stochastic Scene Layout Generation from a Label Set
https://arxiv.org/abs/1907.10719
  1. Co-Evolutionary Compression for Unpaired Image Translation
https://arxiv.org/abs/1907.10804
  1. Enhancing Adversarial Example Transferability with an Intermediate Level Attack
https://arxiv.org/abs/1907.10823
  1. Simultaneous multi-view instance detection with learned geometric soft-constraints
https://arxiv.org/abs/1907.10892
  1. Gated2Depth: Real-time Dense Lidar from Gated Images
https://www.cs.princeton.edu/~fheide/papers/Gated2Depth_preprint.pdf
  1. Moment Matching for Multi-Source Domain Adaptation
https://arxiv.org/abs/1812.01754
  1. Learning Compositional Representations for Few-Shot Recognition
https://sites.google.com/view/comprepr/home
  1. Digging Into Self-Supervised Monocular Depth Estimation
https://arxiv.org/pdf/1806.01260.pdf
  1. Deep Interpretable Non-Rigid Structure from Motion
https://arxiv.org/pdf/1902.10840.pdf
  1. PRECOG: PREdiction Conditioned On Goals in Visual Multi-Agent Settings
https://arxiv.org/pdf/1905.01296.pdf
  1. Lifelong GAN: Continual Learning for Conditional Image Generation
https://arxiv.org/abs/1907.10107
  1. Cap2Det: Learning to Amplify Weak Caption Supervision for Object Detection
https://arxiv.org/abs/1907.10164
  1. Towards Adversarially Robust Object Detection
https://arxiv.org/abs/1907.10310
  1. 6-DOF GraspNet: Variational Grasp Generation for Object Manipulation
https://arxiv.org/abs/1905.10520
  1. Analyzing the Variety Loss in the Context of Probabilistic Trajectory Prediction
https://arxiv.org/abs/1907.10178
  1. DAFL: Data-Free Learning of Student Networks
https://arxiv.org/abs/1904.01186
  1. Multi-adversarial Faster-RCNN for Unrestricted Object Detection
https://arxiv.org/abs/1907.10343
  1. Boosting Few-Shot Visual Learning with Self-Supervision
https://arxiv.org/abs/1906.05186
  1. A Quaternion-based Certifiably Optimal Solution to the Wahba Problem with Outliers
https://arxiv.org/abs/1905.12536
  1. Embodied Visual Recognition
  2. Rethinking ImageNet Pre-training
https://arxiv.org/abs/1811.08883
  1. TensorMask: A Foundation for Dense Object Segmentation
https://arxiv.org/abs/1903.12174
  1. 3D Point Cloud Learning for Large-scale Environment Analysis and Place Recognition
https://arxiv.org/abs/1812.07050
  1. Selectivity or Invariance: Boundary-aware Salient Object Detection
https://arxiv.org/pdf/1812.10066.pdf
  1. Creativity Inspired Zero-Shot Learning
https://arxiv.org/abs/1904.01109
  1. HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips
https://arxiv.org/abs/1906.03327
  1. Correlation Congruence for Knowledge Distillation
https://arxiv.org/abs/1904.018029
  1. VATEX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research
https://arxiv.org/abs/1904.03493
  1. Episodic Training for Domain Generalization
https://arxiv.org/abs/1902.00113
  1. GarNet: A Two-stream Network for Fast and Accurate 3D Cloth Draping
https://arxiv.org/abs/1811.10983v2
  1. Semi-supervised Domain Adaptation via Minimax Entropy
https://arxiv.org/abs/1904.06487
  1. xR-EgoPose: Egocentric 3D Human Pose from an HMD Camera
https://arxiv.org/abs/1907.10045
  1. Canonical Surface Mapping via Geometric Cycle Consistency
https://arxiv.org/abs/1907.10043
  1. Incremental Class Discovery for Semantic Segmentation with RGBD Sensing
https://arxiv.org/abs/1907.10008
  1. U4D: Unsupervised 4D Dynamic Scene Understanding
https://arxiv.org/abs/1907.09905
  1. BMN: Boundary-Matching Network for Temporal Action Proposal Generation
https://arxiv.org/abs/1907.09702
  1. SPGNet: Semantic Prediction Guidance for Scene Parsing
https://arxiv.org/abs/1908.09798
  1. Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation
https://arxiv.org/abs/1811.07456
  1. DUP-Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds Defense
https://arxiv.org/abs/1812.11017
  1. Closed-Form Optimal Two-View Triangulation Based on Angular Errors
https://arxiv.org/abs/1903.09115
  1. Learning Combinatorial Embedding Networks for Deep Graph Matching
https://arxiv.org/abs/1904.00597
  1. A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification
https://arxiv.org/abs/1904.03425
  1. Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement
https://arxiv.org/abs/1907.11921
  1. Symmetry-constrained Rectification Network for Scene Text Recognition
https://arxiv.org/abs/1908.01957
  1. STM: SpatioTemporal and Motion Encoding for Action Recognition
https://arxiv.org/abs/1908.02486
  1. Explicit Shape Encoding for Real-Time Instance Segmentation
https://arxiv.org/abs/1908.04067
  1. Few-Shot Learning with Global Class Representations
https://arxiv.org/abs/1908.05257
  1. Symmetric Cross Entropy for Robust Learning with Noisy Labels
https://arxiv.org/abs/1908.06112
  1. Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation
https://arxiv.org/abs/1908.07172
  1. DADA: Depth-Aware Domain Adaptation in Semantic Segmentation
https://arxiv.org/abs/1904.01886

增加35篇包含开源代码的ICCV2019

  1. Bidirectional One-Shot Unsupervised Domain Mapping
https://github.com/tomercohen11/BiOST
  1. Joint Monocular 3D Detection and Tracking
https://arxiv.org/abs/1811.10742
https://github.com/ucbdrive/3d-vehicle-tracking
  1. MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation
https://arxiv.org/abs/1906.06059
https://github.com/vita-epfl/monoloco
  1. Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data
https://github.com/xw-hu/Mask-ShadowGAN
  1. Towards High-Resolution Salient Object Detection
https://arxiv.org/abs/1908.07274
https://github.com/yi94code/HRSOD
  1. Confidence Regularized Self-Training
https://arxiv.org/abs/1908.09822
https://github.com/yzou2/CRST
  1. Optimizing the F-measure for Threshold-free Salient Object Detectionhttp://data.kaizhao.net/publications/iccv2019fmeasure.pdf
https://github.com/zeakey/iccv2019-fmeasure
  1. Perspective-Guided Convolution Networks for Crowd Counting
https://github.com/Zhaoyi-Yan/PGCNet
  1. End-to-End Wireframe Parsing
https://arxiv.org/abs/1905.03246
https://github.com/zhou13/lcnn
  1. Temporal Attentive Alignment for Large-Scale Video Domain Adaptation
https://arxiv.org/abs/1907.12743http://github.com/cmhungsteve/TA3N
  1. From Open Set to Closed Set: Counting Objects by Spatial Divide-and-Conquer
https://arxiv.org/abs/1908.06473
https://github. com/xhp-hust-2018-2011/S-DCNet
  1. Free-form Video Inpainting with 3D Gated Convolution and Temporal PatchGAN
https://arxiv.org/abs/1904.10247
https://github.com/amjltc295/Free-Form-Video-Inpainting
  1. What Would You Expect? Anticipating Egocentric Actions with Rolling-Unrolling LSTMs and Modality Attention
https://arxiv.org/pdf/1905.09035.pdf
https://github.com/antoninofurnari/rulstm
  1. CompenNet++: End-to-end Full Projector Compensation
https://github.com/BingyaoHuang/CompenNet-plusplus
  1. Pose-aware Dynamic Attention for Human Object Interaction Detection
https://github.com/bobwan1995/Pose-aware-Dynamic-Attention-for-Human-Object-Interaction-Detection
  1. Temporally-Aggregating Spatial Encoder-Decoder for Video Saliency Detection
https://github.com/kylemin/TASED-Net
  1. PU-GAN: a Point Cloud Upsampling Adversarial Network
https://arxiv.org/abs/1907.10844
https://github.com/liruihui/PU-GAN
  1. A Closed-form Solution to Universal Style Transfer
https://arxiv.org/abs/1906.00668
https://github.com/lu-m13/OptimalStyleTransfer
  1. Video Face Clustering with Unknown Number of Clusters
https://github.com/makarandtapaswi/BallClustering_ICCV2019
  1. TSM: Temporal Shift Module for Efficient Video Understanding
https://arxiv.org/abs/1811.08383
https://github.com/mit-han-lab/temporal-shift-module
  1. Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image
https://arxiv.org/abs/1907.11346
https://github.com/mks0601/3DMPPE_ROOTNET_RELEASE
  1. 3D-RelNet: Joint Object and Relational Network for 3D Prediction
https://arxiv.org/pdf/1906.02729.pdf
https://github.com/nileshkulkarni/relative3d
  1. Few-shot Unsupervised Image-to-Image Translation
https://arxiv.org/abs/1905.01723
https://github.com/nvlabs/FUNIT/
  1. Metric Learning with HORDE: High-Order Regularizer for Deep Embeddings
https://arxiv.org/abs/1908.02735
https://github.com/pierre-jacob/ICCV2019-Horde
  1. Model Vulnerability to Distributional Shifts over Image Transformation Sets
https://arxiv.org/abs/1903.11900
https://github.com/ricvolpi/domain-shift-robustness
  1. Language-Conditioned Graph Networks for Relational Reasoning
https://arxiv.org/abs/1905.04405
https://github.com/ronghanghu/lcgn
  1. Domain Intersection and Domain Difference
https://github.com/sagiebenaim/DomainIntersectionDifference
  1. Probabilistic Face Embeddings
https://arxiv.org/abs/1904.09658
https://github.com/seasonSH/Probabilistic-Face-Embeddings
  1. Counting with Focus for Free
https://arxiv.org/abs/1903.12206
https://github.com/shizenglin/Counting-with-Focus-for-Free
  1. CCNet: Criss-Cross Attention for Semantic Segmentation
https://arxiv.org/abs/1811.11721
https://github.com/speedinghzl/CCNet
  1. ABD-Net: Attentive but Diverse Person Re-Identification
https://arxiv.org/abs/1908.01114
https://github.com/TAMU-VITA/ABD-Net
  1. AutoGAN: Neural Architecture Search for Generative Adversarial Networks
https://github.com/TAMU-VITA/AutoGAN
  1. SO-HandNet: Self-Organizing Network for 3D Hand Pose Estimation with Semi-supervised Learning
https://github.com/TerenceCYJ/SO-HandNet
  1. Tex2Shape: Detailed Full Human Body Geometry from a Single Image
https://arxiv.org/abs/1904.08645
https://github.com/thmoa/tex2shape
  1. FCOS: Fully Convolutional One-Stage Object Detectio
https://arxiv.org/abs/1904.01355
https://github.com/tianzhi0549/FCOS/

ICCV 1998-2017最佳论文

2017Mask R-CNNKaiming He, Facebook AI Research; et al.
Georgia Gkioxari, Facebook AI Research
Piotr Dollar, Facebook AI Research
Ross Girshick, Facebook AI Research
2015Deep Neural Decision ForestsPeter Kontschieder, Microsoft Research; et al.
Madalina Fiterau, Carnegie Mellon University
Antonio Criminisi, Microsoft Research
Samuel Rota Bulò, Microsoft Research
2013From Large Scale Image Categorization to Entry-Level CategoriesVicente Ordonez, University of North Carolina at Chapel Hill; et al.
Jia Deng, Stanford University
Yejin Choi, Stony Brook University
Alexander Berg, University of North Carolina at Chapel Hill
Tamara Berg, University of North Carolina at Chapel Hill
2011Relative AttributesDevi Parikh, Toyota Technological Institute at Chicago
Kristen Grauman, University of Texas at Austin2009Discriminative models for multi-class object layoutChaitanya Desai, University of California Irvine; et al.
Deva Ramanan, University of California Irvine
Charless Fowlkes, University of California Irvine
2007Population Shape Regression From Random Design DataBradley Davis, University of North Carolina at Chapel Hill; et al.
P. Thomas Fletcher, University of Utah
Elizabeth Bullitt, University of North Carolina at Chapel Hill
Sarang Joshi, University of Utah
2005Globally Optimal Estimates for Geometric Reconstruction ProblemsFredrik Kahl, Lund University
Didier Henrion, LAAS-CNRS2003Detecting Pedestrians using Patterns of Motion and AppearancePaul Viola, Microsoft Research; et al.
Michael J. Jones, Mitsubishi Electric Research Laboratories
Daniel Snow, Mitsubishi Electric Research Laboratories
Image Parsing: Unifying Segmentation, Detection and RecognitionZhuowen Tu, University of California Los Angeles; et al.
Xiangrong Chen, University of California Los Angeles
Alan L. Yuille, University of California Los Angeles
Song-Chun Zhu, University of California Los Angeles
Image-based Rendering using Image-based PriorsAndrew Fitzgibbon, University of Oxford; et al.
Yonatan Wexler, Weizmann Institute of Science
Andrew Zisserman, University of Oxford
2001Probabilistic Tracking with Exemplars in a Metric SpaceKentaro Toyama & Andrew Blake, Microsoft ResearchThe Space of All Stereo ImagesSteven Seitz, University of Washington1999Euclidean Reconstruction and Reprojection up to SubgroupsYi Ma, University of California Berkeley; et al.
Stefano Soatto, Washington University in St. Louis
Jana Kosecka, University of California Berkeley
Shankar Sastry, University of California Berkeley
A Theory of Shape by Space CarvingKiriakos Kutulakos, University of Rochester
Steven Seitz, Carnegie Mellon University1998Self-Calibration and Metric Reconstruction in spite of Varying and Unknown Internal Camera Paramet...Marc Pollefeys, Katholieke Universiteit Leuven; et al.
Reinhard Koch, Katholieke Universiteit Leuven
Luc Van Gool, Katholieke Universiteit Leuven
The Problem of Degeneracy in Structure and Motion Recovery from Uncalibrated Image SequencesPhil Torr, Microsoft Research; et al.
Andrew Fitzgibbon, University of Oxford
Andrew Zisserman, University of Oxford

对应表格版
2017 Mask R-CNN Kaiming He, Facebook AI Research; et al.
2015 Deep Neural Decision Forests Peter Kontschieder, Microsoft Research; et al.
2013 From Large Scale Image Categorization to Entry-Level Categories Vicente Ordonez, University of North Carolina at Chapel Hill; et al.
2011 Relative Attributes Devi Parikh, Toyota Technological Institute at Chicago
Kristen Grauman, University of Texas at Austin
2009 Discriminative models for multi-class object layout Chaitanya Desai, University of California Irvine; et al.
2007 Population Shape Regression From Random Design Data Bradley Davis, University of North Carolina at Chapel Hill; et al.
2005 Globally Optimal Estimates for Geometric Reconstruction Problems Fredrik Kahl, Lund University
2003 Detecting Pedestrians using Patterns of Motion and Appearance Paul Viola, Microsoft Research; et al.
Image Parsing: Unifying Segmentation, Detection and Recognition Zhuowen Tu, University of California Los Angeles; et al.
Image-based Rendering using Image-based Priors Andrew Fitzgibbon, University of Oxford; et al.
2001 Probabilistic Tracking with Exemplars in a Metric Space Kentaro Toyama & Andrew Blake, Microsoft Research
The Space of All Stereo Images Steven Seitz, University of Washington
1999 Euclidean Reconstruction and Reprojection up to Subgroups Yi Ma, University of California Berkeley; et al.
A Theory of Shape by Space Carving Kiriakos Kutulakos, University of Rochester
Steven Seitz, Carnegie Mellon University
1998 Self-Calibration and Metric Reconstruction in spite of Varying and Unknown Internal Camera Paramet... Marc Pollefeys, Katholieke Universiteit Leuven; et al.
The Problem of Degeneracy in Structure and Motion Recovery from Uncalibrated Image Sequences Phil Torr, Microsoft Research; et al.

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