Github持续更新（8月29日更新200篇）：

（论文下载百度云见文末）

https://github.com/Sophia-11/Awesome-ICCV2019

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

ICCV简介
ICCV录用编号
起源人工智能研究院28篇
旷视11篇
2019ICCVOral31篇
增加116篇ICCV2019文章
增加35篇包含开源代码的ICCV2019

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%

论文接收序号：

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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/

Unsupervised Video Object Segmentation via Attentive Graph Neural Networks
DUAL-GLOWs: Conditional Flow-Based Generative Models for Inter-Modality Transfer in Brain Imaging
Unsupervised Graph Association for Person Re-identification
Relational Attention Network for Crowd Counting
Attentional Neural Fields for Crowd Counting
Learning Compositional Neural Information Fusion for Human Parsing
RANet: Ranking Attention Network for Fast Video Object Segmentation
Learning to Mask Visible Regions for Occluded Pedestrian Detection
Boosted Feature Guided Refinement Network for Single-Shot Detection
Deep Contextual Attention for Human-Object Interaction Detection
Learning the Model Update for Siamese Trackers
3C-Net: Category Count and Center Loss for Weakly-Supervised Action Localization
Learning Rich Features at High-Speed for Single-Shot Object Detection
Transductive learning for zero-shot object detection
Ground-to-aerial Image Geo-localization with a Hard Exemplar Reweighting Triplet Loss
Towards Bridging Semantic Gap to Improve Semantic Segmentation
Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks
Motion Deblurring via Human-Aware Attention Network
Gaussian Affinity for Max-margin Class Imbalanced Learning
A Deep Step Pattern Representation for Multimodal Retinal Image Registration
SegEQA: Video Segmentation based Visual Attention for Embodied Question Answering
Reciprocal Multi-Layer Subspace Learning for Multi-View Clustering
Scoot: A Perceptual Metric for Facial Sketches
EGNet: Edge Guidance Network for Salient Object Detection
PointAE: Point Auto-encoder for 3D Statistical Shape and Texture Modelling
Understanding Human Gaze Communication by Spatio-temporal Graph Reasoning
Optimizing the F-measure for Threshold-free Salient Object Detection
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

Interpolated Convolutional Networks for 3D Point Cloud Understanding

https://arxiv.org/abs/1908.04512

Memory-Based Neighbourhood Embedding for Visual Recognition

https://arxiv.org/abs/1908.04992

Learning Trajectory Dependencies for Human Motion Prediction

https://arxiv.org/abs/1908.05436

Domain Adaptation for Structured Output via Discriminative Patch Representations

https://arxiv.org/abs/1901.05427

Deep Non-Rigid Structure from Motion

https://arxiv.org/abs/1908.00052

Scalable Place Recognition Under Appearance Change for Autonomous Driving

https://arxiv.org/abs/1908.00178

Restoration of Non-rigidly Distorted Underwater Images using a Combination of Compressive Sensing and Local Polynomial Image Representations

https://arxiv.org/abs/1908.01940

Consensus Maximization Tree Search Revisited

https://arxiv.org/abs/1908.02021

Weakly Supervised Energy-Based Learning for Action Segmentation
Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification

https://arxiv.org/abs/1811.10144

Controllable Artistic Text Style Transfer via Shape-Matching GAN

https://arxiv.org/abs/1905.01354

Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition

https://arxiv.org/abs/1907.13369

Expectation-Maximization Attention Networks for Semantic Segmentation

https://arxiv.org/abs/1907.13426

VideoBERT: A Joint Model for Video and Language Representation Learning

https://arxiv.org/abs/1904.01766

CARAFE: Content-Aware ReAssembly of FEatures

https://arxiv.org/pdf/1905.02188.pdf

Habitat: A Platform for Embodied AI Research

https://arxiv.org/abs/1904.01201

Equivariant Multi-View Networks

https://arxiv.org/abs/1904.00993

PointFlow : 3D Point Cloud Generation with Continuous Normalizing Flows

https://arxiv.org/abs/1906.12320

Learnable Triangulation of Human Pose

https://arxiv.org/abs/1905.05754

Learning Implicit Generative Models by Matching Perceptual Features

https://arxiv.org/abs/1904.02762v1

COCO-GAN: Generation by Parts via Conditional Coordinating

https://arxiv.org/abs/1904.00284

SlowFast Networks for Video Recognition

https://arxiv.org/abs/1812.03982

Exploring Randomly Wired Neural Networks for Image Recognition

https://arxiv.org/abs/1904.01569

Can GCNs Go as Deep as CNNs?

https://arxiv.org/abs/1904.03751

Deep SR-ITM: Joint Learning of Super-resolution and Inverse Tone-Mapping for 4K UHD HDR Applications

https://arxiv.org/abs/1904.11176

Meta-Sim Learning to Generate Synthetic Datasets

https://arxiv.org/abs/1904.11621

Deep HoughVoting for 3D Object Detection in Point Clouds

https://arxiv.org/abs/1904.09664

Variational Adversarial Active Learning

https://arxiv.org/abs/1904.00370

Towards Unconstrained End-to-End Text Spotting

https://arxiv.org/abs/1908.09231

Non-local Recurrent Neural Memory for Supervised Sequence Modeling

https://arxiv.org/abs/1908.09535

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

Similarity-Preserving Knowledge Distillation

https://arxiv.org/abs/1907.09682

GA-DAN: Geometry-Aware Domain Adaptation Network for Scene Text Detection and Recognition

https://arxiv.org/abs/1907.09653

Tell, Draw, and Repeat: Generating and modifying images based on continual linguistic instruction

https://arxiv.org/pdf/1811.09845.pdf

Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers

https://arxiv.org/abs/1904.08489

nocaps: novel object captioning at scale

https://arxiv.org/abs/1812.08658

ThunderNet: Towards Real-time Generic Object Detection

https://arxiv.org/abs/1903.11752

Scene GraphPrediction with Limited Labels

https://arxiv.org/abs/1904.11622

Ego-Pose Estimation and Forecasting as Real-Time PD Control

https://arxiv.org/abs/1906.03173

The Trajectron: Probabilistic Multi-Agent Trajectory Modeling withDynamic Spatiotemporal Graphs

https://arxiv.org/abs/1810.05993

End-to-End Learning of Representations for Asynchronous Event-BasedData

https://arxiv.org/abs/1904.08245

Efficient Learning on Point Clouds with Basis Point Sets

https://arxiv.org/abs/1908.09186

Dynamic Kernel Distillation for Efficient Pose Estimation in Videos

https://arxiv.org/abs/1908.09216

Single-Stage Multi-Person Pose Machines

https://arxiv.org/abs/1908.09220

Towards Unsupervised Image Captioning with Shared Multimodal Embeddings

https://arxiv.org/abs/1908.09317

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns

https://arxiv.org/abs/1908.09327

Shape-Aware Human Pose and Shape Reconstruction Using Multi-View Images

https://arxiv.org/abs/1908.09464

Relation Distillation Networks for Video Object Detection

https://arxiv.org/abs/1908.09511

Object-Driven Multi-Layer Scene Decomposition From a Single Image

https://arxiv.org/abs/1908.09521

Embarrassingly Simple Binary Representation Learning

https://arxiv.org/abs/1908.09573

Moulding Humans: Non-parametric 3D Human Shape Estimation from Single Images

https://arxiv.org/abs/1908.00439

Learning the Model Update for Siamese Trackers

https://arxiv.org/abs/1908.00855

Distilling Knowledge From a Deep Pose Regressor Network

https://arxiv.org/abs/1908.00858

Permutation-invariant Feature Restructuring for Correlation-aware Image Set-based Recognition

https://arxiv.org/abs/1908.01174

ARGAN: Attentive Recurrent Generative Adversarial Network for Shadow Detection and Removal

https://arxiv.org/abs/1908.01323

Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation

https://arxiv.org/abs/1908.01491

View N-gram Network for 3D Object Retrieval

https://arxiv.org/abs/1908.01958

Semi-supervised Skin Detection by Network with Mutual Guidance

https://arxiv.org/abs/1908.01977

Deep Self-Learning From Noisy Labels

https://arxiv.org/abs/1908.02160

Learning Aberrance Repressed Correlation Filters for Real-Time UAV Tracking

https://arxiv.org/abs/1908.02231

Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning

https://arxiv.org/abs/1908.02441

Expert Sample Consensus Applied to Camera Re-Localization

https://arxiv.org/abs/1908.02484

SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition

https://arxiv.org/abs/1908.02660

GP2C: Geometric Projection Parameter Consensus for Joint 3D Pose and Focal Length Estimation in the Wild

https://arxiv.org/abs/1908.02809

SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

https://arxiv.org/abs/1904.01416

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

Orientation-aware Semantic Segmentation on Icosahedron Spheres

https://arxiv.org/abs/1907.12849

EMPNet: Neural Localisation and Mapping using Embedded Memory Points

https://arxiv.org/abs/1907.13268

SceneGraphNet: Neural Message Passing for 3D Indoor Scene Augmentation

https://arxiv.org/abs/1907.11308

On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method

https://arxiv.org/abs/1907.11684

Goal-Driven Sequential Data Abstraction

https://arxiv.org/abs/1907.12336

Recursive Cascaded Networks for Unsupervised Medical Image Registration

https://arxiv.org/abs/1907.12353

Learn to Scale: Generating Multipolar Normalized Density Map for Crowd Counting

https://arxiv.org/abs/1907.12428

HoloGAN: Unsupervised learning of 3D representations from natural images

https://arxiv.org/abs/1904.01326

MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning

https://arxiv.org/abs/1903.10258

FrameNet: Learning Local Canonical Frames of 3D Surfaces from a Single RGB Image

https://arxiv.org/pdf/1903.12305.pdf

Face De-occlusion using 3D Morphable Model and Generative Adversarialhttp://image.inha.ac.kr/paper/ICCV2019_Xaiowei.pdf
Deep Meta Learning for Real-Time Target-Aware Visual Tracking

https://arxiv.org/pdf/1712.09153.pdf

Switchable Whitening for Deep Representation Learning

https://arxiv.org/abs/1904.09739

Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution

https://arxiv.org/abs/1904.05049

Multi-layer Depth and Epipolar Feature Transformers for 3D Scene Reconstruction

https://arxiv.org/abs/1902.06729

Task2Vec: Task Embedding for Meta-Learning

https://arxiv.org/abs/1902.03545

ACE: Adapting to Changing Environments for Semantic Segmentation

https://arxiv.org/pdf/1904.06268.pdf

Few-shot Object Detection via Feature Reweighting

https://arxiv.org/pdf/1812.01866.pdf

Disentangling Propagation and Generation for Video Prediction

https://arxiv.org/pdf/1812.00452.pdf

An Empirical Study of Spatial Attention Mechanisms in Deep Networks

https://arxiv.org/pdf/1904.05873.pdf

Fashion++: Minimal Edits for Outfit Improvement

https://arxiv.org/pdf/1904.09261.pdf

Align2Ground: Weakly Supervised Phrase Grounding Guided by Image-Caption Alignment

https://arxiv.org/pdf/1903.11649.pdf

Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded

https://arxiv.org/pdf/1902.03751.pdf

SplitNet: Sim2Sim and Task2Task Transfer for Embodied Visual Navigation

https://arxiv.org/pdf/1905.07512.pdf

EM-Fusion: Dynamic Object-Level SLAM with Probabilistic Data Association

https://arxiv.org/abs/1904.11781

Texture Fields: Learning Texture Representations in Function Space

https://arxiv.org/abs/1905.07259

AMASS: Archive of Motion Capture as Surface Shapes

https://arxiv.org/abs/1904.03278

End-to-end Learning for Graph Decomposition

https://arxiv.org/pdf/1812.09737.pdf

Towards Multi-pose Guided Virtual Try-on Network

https://arxiv.org/abs/1902.11026

Learning to Reconstruct 3D Manhattan Wireframes from a Single Image

https://arxiv.org/abs/1905.07482

Coherent Semantic Attention for Image Inpainting

https://arxiv.org/abs/1905.12384

LayoutVAE: Stochastic Scene Layout Generation from a Label Set

https://arxiv.org/abs/1907.10719

Co-Evolutionary Compression for Unpaired Image Translation

https://arxiv.org/abs/1907.10804

Enhancing Adversarial Example Transferability with an Intermediate Level Attack

https://arxiv.org/abs/1907.10823

Simultaneous multi-view instance detection with learned geometric soft-constraints

https://arxiv.org/abs/1907.10892

Gated2Depth: Real-time Dense Lidar from Gated Images

https://www.cs.princeton.edu/~fheide/papers/Gated2Depth_preprint.pdf

Moment Matching for Multi-Source Domain Adaptation

https://arxiv.org/abs/1812.01754

Learning Compositional Representations for Few-Shot Recognition

https://sites.google.com/view/comprepr/home

Digging Into Self-Supervised Monocular Depth Estimation

https://arxiv.org/pdf/1806.01260.pdf

Deep Interpretable Non-Rigid Structure from Motion

https://arxiv.org/pdf/1902.10840.pdf

PRECOG: PREdiction Conditioned On Goals in Visual Multi-Agent Settings

https://arxiv.org/pdf/1905.01296.pdf

Lifelong GAN: Continual Learning for Conditional Image Generation

https://arxiv.org/abs/1907.10107

Cap2Det: Learning to Amplify Weak Caption Supervision for Object Detection

https://arxiv.org/abs/1907.10164

Towards Adversarially Robust Object Detection

https://arxiv.org/abs/1907.10310

6-DOF GraspNet: Variational Grasp Generation for Object Manipulation

https://arxiv.org/abs/1905.10520

Analyzing the Variety Loss in the Context of Probabilistic Trajectory Prediction

https://arxiv.org/abs/1907.10178

DAFL: Data-Free Learning of Student Networks

https://arxiv.org/abs/1904.01186

Multi-adversarial Faster-RCNN for Unrestricted Object Detection

https://arxiv.org/abs/1907.10343

Boosting Few-Shot Visual Learning with Self-Supervision

https://arxiv.org/abs/1906.05186

A Quaternion-based Certifiably Optimal Solution to the Wahba Problem with Outliers

https://arxiv.org/abs/1905.12536

Embodied Visual Recognition
Rethinking ImageNet Pre-training

https://arxiv.org/abs/1811.08883

TensorMask: A Foundation for Dense Object Segmentation

https://arxiv.org/abs/1903.12174

3D Point Cloud Learning for Large-scale Environment Analysis and Place Recognition

https://arxiv.org/abs/1812.07050

Selectivity or Invariance: Boundary-aware Salient Object Detection

https://arxiv.org/pdf/1812.10066.pdf

Creativity Inspired Zero-Shot Learning

https://arxiv.org/abs/1904.01109

HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips

https://arxiv.org/abs/1906.03327

Correlation Congruence for Knowledge Distillation

https://arxiv.org/abs/1904.018029

VATEX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research

https://arxiv.org/abs/1904.03493

Episodic Training for Domain Generalization

https://arxiv.org/abs/1902.00113

GarNet: A Two-stream Network for Fast and Accurate 3D Cloth Draping

https://arxiv.org/abs/1811.10983v2

Semi-supervised Domain Adaptation via Minimax Entropy

https://arxiv.org/abs/1904.06487

xR-EgoPose: Egocentric 3D Human Pose from an HMD Camera

https://arxiv.org/abs/1907.10045

Canonical Surface Mapping via Geometric Cycle Consistency

https://arxiv.org/abs/1907.10043

Incremental Class Discovery for Semantic Segmentation with RGBD Sensing

https://arxiv.org/abs/1907.10008

U4D: Unsupervised 4D Dynamic Scene Understanding

https://arxiv.org/abs/1907.09905

BMN: Boundary-Matching Network for Temporal Action Proposal Generation

https://arxiv.org/abs/1907.09702

SPGNet: Semantic Prediction Guidance for Scene Parsing

https://arxiv.org/abs/1908.09798

Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation

https://arxiv.org/abs/1811.07456

DUP-Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds Defense

https://arxiv.org/abs/1812.11017

Closed-Form Optimal Two-View Triangulation Based on Angular Errors

https://arxiv.org/abs/1903.09115

Learning Combinatorial Embedding Networks for Deep Graph Matching

https://arxiv.org/abs/1904.00597

A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification

https://arxiv.org/abs/1904.03425

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

Symmetry-constrained Rectification Network for Scene Text Recognition

https://arxiv.org/abs/1908.01957

STM: SpatioTemporal and Motion Encoding for Action Recognition

https://arxiv.org/abs/1908.02486

Explicit Shape Encoding for Real-Time Instance Segmentation

https://arxiv.org/abs/1908.04067

Few-Shot Learning with Global Class Representations

https://arxiv.org/abs/1908.05257

Symmetric Cross Entropy for Robust Learning with Noisy Labels

https://arxiv.org/abs/1908.06112

Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation

https://arxiv.org/abs/1908.07172

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

Bidirectional One-Shot Unsupervised Domain Mapping

https://github.com/tomercohen11/BiOST

Joint Monocular 3D Detection and Tracking

https://arxiv.org/abs/1811.10742

https://github.com/ucbdrive/3d-vehicle-tracking

MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation

https://arxiv.org/abs/1906.06059

https://github.com/vita-epfl/monoloco

Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data

https://github.com/xw-hu/Mask-ShadowGAN

Towards High-Resolution Salient Object Detection

https://arxiv.org/abs/1908.07274

https://github.com/yi94code/HRSOD

Confidence Regularized Self-Training

https://arxiv.org/abs/1908.09822

https://github.com/yzou2/CRST

Optimizing the F-measure for Threshold-free Salient Object Detectionhttp://data.kaizhao.net/publications/iccv2019fmeasure.pdf

https://github.com/zeakey/iccv2019-fmeasure

Perspective-Guided Convolution Networks for Crowd Counting

https://github.com/Zhaoyi-Yan/PGCNet

End-to-End Wireframe Parsing

https://arxiv.org/abs/1905.03246

https://github.com/zhou13/lcnn

Temporal Attentive Alignment for Large-Scale Video Domain Adaptation

https://arxiv.org/abs/1907.12743http://github.com/cmhungsteve/TA3N

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

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

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

CompenNet++: End-to-end Full Projector Compensation

https://github.com/BingyaoHuang/CompenNet-plusplus

Pose-aware Dynamic Attention for Human Object Interaction Detection

https://github.com/bobwan1995/Pose-aware-Dynamic-Attention-for-Human-Object-Interaction-Detection

Temporally-Aggregating Spatial Encoder-Decoder for Video Saliency Detection

https://github.com/kylemin/TASED-Net

PU-GAN: a Point Cloud Upsampling Adversarial Network

https://arxiv.org/abs/1907.10844

https://github.com/liruihui/PU-GAN

A Closed-form Solution to Universal Style Transfer

https://arxiv.org/abs/1906.00668

https://github.com/lu-m13/OptimalStyleTransfer

Video Face Clustering with Unknown Number of Clusters

https://github.com/makarandtapaswi/BallClustering_ICCV2019

TSM: Temporal Shift Module for Efficient Video Understanding

https://arxiv.org/abs/1811.08383

https://github.com/mit-han-lab/temporal-shift-module

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

3D-RelNet: Joint Object and Relational Network for 3D Prediction

https://arxiv.org/pdf/1906.02729.pdf

https://github.com/nileshkulkarni/relative3d

Few-shot Unsupervised Image-to-Image Translation

https://arxiv.org/abs/1905.01723

https://github.com/nvlabs/FUNIT/

Metric Learning with HORDE: High-Order Regularizer for Deep Embeddings

https://arxiv.org/abs/1908.02735

https://github.com/pierre-jacob/ICCV2019-Horde

Model Vulnerability to Distributional Shifts over Image Transformation Sets

https://arxiv.org/abs/1903.11900

https://github.com/ricvolpi/domain-shift-robustness

Language-Conditioned Graph Networks for Relational Reasoning

https://arxiv.org/abs/1905.04405

https://github.com/ronghanghu/lcgn

Domain Intersection and Domain Difference

https://github.com/sagiebenaim/DomainIntersectionDifference

Probabilistic Face Embeddings

https://arxiv.org/abs/1904.09658

https://github.com/seasonSH/Probabilistic-Face-Embeddings

Counting with Focus for Free

https://arxiv.org/abs/1903.12206

https://github.com/shizenglin/Counting-with-Focus-for-Free

CCNet: Criss-Cross Attention for Semantic Segmentation

https://arxiv.org/abs/1811.11721

https://github.com/speedinghzl/CCNet

ABD-Net: Attentive but Diverse Person Re-Identification

https://arxiv.org/abs/1908.01114

https://github.com/TAMU-VITA/ABD-Net

AutoGAN: Neural Architecture Search for Generative Adversarial Networks

https://github.com/TAMU-VITA/AutoGAN

SO-HandNet: Self-Organizing Network for 3D Hand Pose Estimation with Semi-supervised Learning

https://github.com/TerenceCYJ/SO-HandNet

Tex2Shape: Detailed Full Human Body Geometry from a Single Image

https://arxiv.org/abs/1904.08645

https://github.com/thmoa/tex2shape

FCOS: Fully Convolutional One-Stage Object Detectio

https://arxiv.org/abs/1904.01355

https://github.com/tianzhi0549/FCOS/

百度云链接：链接：https://pan.baidu.com/s/1JnbZFmQwtqk1mQMN-ZpAOw
提取码：mv56

如果百度云失效了，去公众号【计算机视觉联盟】后台回复关键词： ICCV2019

或在本条下方评论，我看到就会回复了

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ICCV 2019 | ICCV 2019 论文接收列表 | ICCV 2019一共接收1077篇 | 共4303篇投稿