CVPR 2017 notes

This is my personal notes and focuses on several aspects as listed below.

3D vision and Deep Learning
Optical Flow
2D/3D feature detection and matching
SLAM
6 DOF Object detection & tracking
Object Detection
Transfer Learning & Domain Adaptation
Computational Photography
3D Reconstruction
RGBD Sensors / Stereo
DL model compression
Sensor Calibration
Image Retrieval
Human Analysis
Face Analysis
Object Tracking
Machine Learning
Multiple View Geometry

Topics not included here but I am also interested with:

Image/video Captioning
Visual Question Answering
Vision & Sports
Edge detection & semantic segmentation
Video / temporal analysis
Denoising/deblurring
Human action analysis
Texture/style network

If you want to see all CVPR 2017 papers, please refer to the CVF open access of all CVPR 2017 papers:

Main Conference Papers
Workshop Papers

Papers by topics

3D vision and Deep Learning

Convolutional Neural Network Architecture for Geometric Matching. INRIA. Ignacio Rocco, Relja ArandjeloviÄ‡, Josef Sivic
Paper
Inverse Compositional Spatial Transformer Networks. Chen-Hsuan Lin, Simon Lucey. Paper
Geometric Loss Functions for Camera Pose Regression with Deep Learning. Alex Kendall, Roberto Cipolla. Paper
Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation. Paper
FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence, Seungryong Kim, Dongbo Min, Bumsub Ham, Sangryul Jeon, Stephen Lin, Kwanghoon Sohn
End-To-End Training of Hybrid CNN-CRF Models for Stereo. Patrick Knobelreiter, Christian Reinbacher, Alexander Shekhovtsov, Thomas Pock
Semi-Supervised Deep Learning for Monocular Depth Map Prediction, Yevhen Kuznietsov, Jörg Stückler, Bastian Leibe
DSAC - Differentiable RANSAC for Camera Localization, Eric Brachmann, Alexander Krull, Sebastian Nowozin, Jamie Shotton, Frank Michel, Stefan Gumhold, Carsten Rother
Learning Non-Maximum Suppression, Jan Hosang, Rodrigo Benenson, Bernt Schiele
Improved Stereo Matching With Constant Highway Networks and Reflective Confidence Learning, Amit Shaked, Lior Wolf

Optical Flow

FlowNet 2.0: Evolution of Optical Flow Estimation With Deep Networks Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia, Margret Keuper, Alexey Dosovitskiy, Thomas Brox Paper Code
Slow Flow: Exploiting High-Speed Cameras for Accurate and Diverse Optical Flow Reference Data, Joel Janai, Fatma Güney, Jonas Wulff, Michael J. Black, Andreas Geiger
CNN-Based Patch Matching for Optical Flow With Thresholded Hinge Embedding Loss, Christian Bailer, Kiran Varanasi, Didier Stricker
Optical Flow Estimation Using a Spatial Pyramid Network, Anurag Ranjan, Michael J. Black
CLKN: Cascaded Lucas-Kanade Networks for Image Alignment, Che-Han Chang, Chun-Nan Chou, Edward Y. Chang
S2F: Slow-To-Fast Interpolator Flow, Yanchao Yang, Stefano Soatto
Filter Flow Made Practical: Massively Parallel and Lock-Free, Sathya N. Ravi, Yunyang Xiong, Lopamudra Mukherjee, Vikas Singh
Accurate Optical Flow via Direct Cost Volume Processing, Jia Xu, René Ranftl, Vladlen Koltun
InterpoNet, a Brain Inspired Neural Network for Optical Flow Dense Interpolation, Shay Zweig, Lior WolfI
Optical Flow in Mostly Rigid Scenes, Jonas Wulff, Laura Sevilla-Lara, Michael J. Black
Optical Flow Requires Multiple Strategies (but Only One Network), Tal Schuster, Lior Wolf, David Gadot

2D/3D feature detection and matching

Comparative Evaluation of Hand-Crafted and Learned Local Features. Johannes L. Schönberger,Hans Hardmeier, Torsten Sattler, Marc Pollefeys
Paper Website
HPatches: A benchmark and evaluation of handcrafted and learned local descriptors, Vassileios Balntas*, Karel Lenc*, Andrea Vedaldi and Krystian Mikolajczyk. Paper Github
GMS: Grid-based Motion Statistics for Fast, Ultra-robust Feature Correspondence. JiaWang Bian, Daniel Lin, Yasuyuki Matsushita, Sai-Kit Yeung, Tan Dat Nguyen, Ming-Ming Cheng Website Github Youtube
3DMatch: Learning Local Geometric Descriptors From RGB-D Reconstructions. Andy Zeng, Shuran Song, Matthias Niessner, Matthew Fisher, Jianxiong Xiao, Thomas Funkhouser
AnchorNet: A Weakly Supervised Network to Learn Geometry-Sensitive Features for Semantic Matching, David Novotny, Diane Larlus, Andrea Vedaldi
Quad-Networks: Unsupervised Learning to Rank for Interest Point Detection, Nikolay Savinov, Akihito Seki, Lubor Ladicky, Torsten Sattler, Marc Pollefeys
Learning Deep Binary Descriptor With Multi-Quantization, Yueqi Duan, Jiwen Lu, Ziwei Wang, Jianjiang Feng, Jie Zhou
Alternating Direction Graph Matching, D. Khuê Lê-Huu, Nikos Paragios
Learning Discriminative and Transformation Covariant Local Feature Detectors, Xu Zhang, Felix X. Yu, Svebor Karaman, Shih-Fu Chang
Deep Semantic Feature Matching, Nikolai Ufer, Björn Ommer
L2-Net: Deep Learning of Discriminative Patch Descriptor in Euclidean Space, Yurun Tian, Bin Fan, Fuchao Wu
SGM-Nets: Semi-Global Matching With Neural Networks, Akihito Seki, Marc Pollefeys

SLAM

CNN-SLAM: Real-time dense monocular SLAM with learned depth prediction Paper
NID-SLAM: Robust Monocular SLAM Using Normalised Information Distance. Geoffrey Pascoe, Will Maddern, Michael Tanner, Pedro Piniés, Paul Newman. Paper
Cognitive Mapping and Planning for Visual Navigation. Saurabh Gupta, James Davidson, Sergey Levine, Rahul Sukthankar, Jitendra Malik Paper Project Code
Visual-Inertial-Semantic Scene Representation for 3D Object Detection Jingming Dong, Xiaohan Fei, Stefano Soatto
On-The-Fly Adaptation of Regression Forests for Online Camera Relocalisation Tommaso Cavallari, Stuart Golodetz, Nicholas A. Lord, Julien Valentin, Luigi Di Stefano, Philip H. S. Torr
DeMoN: Depth and Motion Network for Learning Monocular Stereo, Benjamin Ummenhofer, Huizhong Zhou, Jonas Uhrig, Nikolaus Mayer, Eddy Ilg, Alexey Dosovitskiy, Thomas Brox
A Dataset for Benchmarking Image-Based Localization, Xun Sun, Yuanfan Xie, Pei Luo, Liang Wang
Event-Based Visual Inertial Odometry, Alex Zihao Zhu, Nikolay Atanasov, Kostas Daniilidis
Are Large-Scale 3D Models Really Necessary for Accurate Visual Localization? Torsten Sattler, Akihiko Torii, Josef Sivic, Marc Pollefeys, Hajime Taira, Masatoshi Okutomi, Tomas Pajdla
Unsupervised Learning of Depth and Ego-Motion From Video, Tinghui Zhou, Matthew Brown, Noah Snavely, David G. Lowe

6 DOF Object detection & tracking

PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning Alexander Krull, Eric Brachmann, Sebastian Nowozin, Frank
Global Hypothesis Generation for 6D Object Pose Estimation. Frank Michel, Alexander Kirillov, Eric Brachmann, Alexander Krull, Stefan Gumhold, Bogdan Savchynskyy, Carsten Rother. Paper
Real-Time 3D Model Tracking in Color and Depth on a Single CPU Core Wadim Kehl, Federico Tombari, Slobodan Ilic, Nassir Navab
BIND: Binary Integrated Net Descriptors for Texture-Less Object Recognition Jacob Chan, Jimmy Addison Lee, Qian Kemao
Real-Time 3D Model Tracking in Color and Depth on a Single CPU Core, Wadim Kehl, Federico Tombari, Slobodan Ilic, Nassir Navab
3D Bounding Box Estimation Using Deep Learning and Geometry, Arsalan Mousavian, Dragomir Anguelov, John Flynn, Jana Košecká

Object Detection

LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems. Qualcomm & UCSD
Paper
Accurate Single Stage Detector Using Recurrent Rolling Convolution. SenseTime Jimmy Ren, Xiaohao Chen, Jianbo Liu, Wenxiu Sun, Jiahao Pang, Qiong Yan, Yu-Wing Tai, Li Xu
Website
Feature Pyramid Networks for Object Detection. Tsung-Yi Lin, Piotr Dollar, Ross Girshick, Kaiming He, Bharath Hariharan, Serge Belongie
Speed/Accuracy Trade-Offs for Modern Convolutional Object Detectors Jonathan Huang, Vivek Rathod, Chen Sun, Menglong Zhu, Anoop Korattikara, Alireza Fathi, Ian Fischer, Zbigniew Wojna, Yang Song, Sergio Guadarrama, Kevin Murphy
Amodal Detection of 3D Objects: Inferring 3D Bounding Boxes From 2D Ones in RGB-Depth Images. Zhuo Deng, Longin Jan Latecki
Object Detection in Videos With Tubelet Proposal Networks, Kai Kang, Hongsheng Li, Tong Xiao, Wanli Ouyang, Junjie Yan, Xihui Liu, Xiaogang Wang
Fast Boosting Based Detection Using Scale Invariant Multimodal Multiresolution Filtered Features, Arthur Daniel Costea, Robert Varga, Sergiu Nedevschi
Perceptual Generative Adversarial Networks for Small Object Detection, Jianan Li, Xiaodan Liang, Yunchao Wei, Tingfa Xu, Jiashi Feng, Shuicheng Yan
FastMask: Segment Multi-Scale Object Candidates in One Shot, Hexiang Hu, Shiyi Lan, Yuning Jiang, Zhimin Cao, Fei Sha
Multiple Instance Detection Network With Online Instance Classifier Refinement, Peng Tang, Xinggang Wang, Xiang Bai, Wenyu Liu
Straight to Shapes: Real-Time Detection of Encoded Shapes, Saumya Jetley, Michael Sapienza, Stuart Golodetz, Philip H. S. Torr
Weakly Supervised Cascaded Convolutional Networks, Ali Diba, Vivek Sharma, Ali Pazandeh, Hamed Pirsiavash, Luc Van Gool
RON: Reverse Connection With Objectness Prior Networks for Object Detection, Tao Kong, Fuchun Sun, Anbang Yao, Huaping Liu, Ming Lu, Yurong Chen
YOLO9000: Better, Faster, Stronger, Joseph Redmon, Ali Farhadi
Multi-View 3D Object Detection Network for Autonomous Driving, Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, Tian Xia
YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video, Esteban Real, Jonathon Shlens, Stefano Mazzocchi, Xin Pan, Vincent Vanhoucke
Learning Detection With Diverse Proposals, Samaneh Azadi, Jiashi Feng, Trevor Darrell

Transfer Learning & Domain Adaptation

Borrowing Treasures From the Wealthy: Deep Transfer Learning Through Selective Joint Fine-Tuning. Weifeng Ge, Yizhou Yu . Paper
Fine-Grained Recognition of Thousands of Object Categories With Single-Example Training, Leonid Karlinsky, Joseph Shtok, Yochay Tzur, Asaf Tzadok
Matrix Tri-Factorization With Manifold Regularizations for Zero-Shot Learning, Xing Xu, Fumin Shen, Yang Yang, Dongxiang Zhang, Heng Tao Shen, Jingkuan Song
Semantically Consistent Regularization for Zero-Shot Recognition, Pedro Morgado, Nuno Vasconcelos
Unified Embedding and Metric Learning for Zero-Exemplar Event Detection. Noureldien Hussein, Efstratios Gavves, Arnold W.M. Smeulders
Growing a Brain: Fine-Tuning by Increasing Model Capacity, Yu-Xiong Wang, Deva Ramanan, Martial Hebert
Zero-Shot Learning - the Good, the Bad and the Ugly,Yongqin Xian, Bernt Schiele, Zeynep Akata
Adversarial Discriminative Domain Adaptation, Eric Tzeng, Judy Hoffman, Kate Saenko, Trevor Darrell
Quality Aware Network for Set to Set Recognition, Yu Liu, Junjie Yan, Wanli Ouyang, Sensetime
Correlational Gaussian Processes for Cross-Domain Visual Recognition, Chengjiang Long, Gang Hua
Zero Shot Learning via Multi-Scale Manifold Regularization, Shay Deutsch, Soheil Kolouri, Kyungnam Kim, Yuri Owechko, Stefano Soatto
Joint Geometrical and Statistical Alignment for Visual Domain Adaptation, Jing Zhang, Wanqing Li, Philip Ogunbona
Deep Hashing Network for Unsupervised Domain Adaptation, Hemanth Venkateswara, Jose Eusebio, Shayok Chakraborty, Sethuraman Panchanathan
Learning Features by Watching Objects Move, Deepak Pathak, Ross Girshick, Piotr Dollár, Trevor Darrell, Bharath Hariharan
From Zero-Shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis, Yang Long, Li Liu, Ling Shao, Fumin Shen, Guiguang Ding, Jungong Han
A Gift From Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning, Junho Yim, Donggyu Joo, Jihoon Bae, Junmo Kim
Domain Adaptation by Mixture of Alignments of Secondor Higher-Order Scatter Tensors, Piotr Koniusz, Yusuf Tas, Fatih Porikli

Computational Photography

A Unified Approach of Multi-scale Deep and Hand-crafted Features for Defocus Estimation. KAIST & Tecent Youtu Paper website
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. Christian Ledig, Lucas Theis, Ferenc HuszÃƒÂ¡r, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi. Paper Code
Depth From Defocus in the Wild, Huixuan Tang, Scott Cohen, Brian Price, Stephen Schiller, Kiriakos N. Kutulakos

3D Reconstruction

Using Locally Corresponding CAD Models for Dense 3D Reconstructions from a Single Image. Chen Kong, Chen-Hsuan Lin, Simon Lucey. Carnegie Mellon University
Paper Github
Multi-View Supervision for Single-View Reconstruction via Differentiable Ray Consistency. Shubham Tulsiani, Tinghui Zhou, Alexei A. Efros, Jitendra Malik
Transformation-Grounded Image Generation Network for Novel 3D View Synthesis, Eunbyung Park, Jimei Yang, Ersin Yumer, Duygu Ceylan, Alexander C. Berg
SurfNet: Generating 3D Shape Surfaces Using Deep Residual Networks, Ayan Sinha, Asim Unmesh, Qixing Huang, Karthik Ramani
HSfM: Hybrid Structure-from-Motion, Hainan Cui, Xiang Gao, Shuhan Shen, Zhanyi Hu
IM2CAD, Hamid Izadinia, Qi Shan, Steven M. Seitz
A Point Set Generation Network for 3D Object Reconstruction From a Single Image, Haoqiang Fan, Hao Su, Leonidas J. Guibas
Learning Category-Specific 3D Shape Models From Weakly Labeled 2D Images, Dingwen Zhang, Junwei Han, Yang Yang, Dong Huang
Self-Calibration-Based Approach to Critical Motion Sequences of Rolling-Shutter Structure From Motion, Eisuke Ito, Takayuki Okatani
KillingFusion: Non-Rigid 3D Reconstruction without Correspondences, Miroslava Slavcheva, Maximilian Baust, Daniel Cremers, Slobodan Ilic
ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes, Angela Dai, Angel X. Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, Matthias Nießner
Unsupervised Monocular Depth Estimation With Left-Right Consistency, Clément Godard, Oisin Mac Aodha, Gabriel J. Brostow

RGBD Sensors / Stereo

Intel RealSense Stereoscopic Depth Cameras. Intel
Paper
Dynamic Time-Of-Flight. Michael Schober, Amit Adam, Omer Yair, Shai Mazor, Sebastian Nowozin

DL model compression

On Compressing Deep Models by Low Rank and Sparse Decomposition, Xiyu Yu, Tongliang Liu, Xinchao Wang, Dacheng Tao
A Compact DNN: Approaching GoogLeNet-Level Accuracy of Classification and Domain Adaptation, Chunpeng Wu, Wei Wen, Tariq Afzal, Yongmei Zhang, Yiran Chen, Hai (Helen) Li
LCNN: Lookup-Based Convolutional Neural Network, Hessam Bagherinezhad, Mohammad Rastegari, Ali Farhad
Budget-Aware Deep Semantic Video Segmentation, Behrooz Mahasseni, Sinisa Todorovic, Alan Fern
Fixed-Point Factorized Networks, Peisong Wang, Jian Cheng
Network Sketching: Exploiting Binary Structure in Deep CNNs, Yiwen Guo, Anbang Yao, Hao Zhao, Yurong Chen
Deep Learning With Low Precision by Half-Wave Gaussian Quantization, Zhaowei Cai, Xiaodong He, Jian Sun, Nuno Vasconcelos
Designing Energy-Efficient Convolutional Neural Networks Using Energy-Aware Pruning, Tien-Ju Yang, YuHsin Chen, Vivienne Sze
Weighted-Entropy-Based Quantization for Deep Neural Networks, Eunhyeok Park, Junwhan Ahn, Sungjoo Yoo
Mimicking Very Efficient Network for Object Detection, Quanquan Li, Shengying Jin, Junjie Yan

Sensor Calibration

A Practical Method for Fully Automatic Intrinsic Camera Calibration Using Directionally Encoded Light, Mahdi Abbaspour Tehrani, Thabo Beeler, Anselm Grundhöfer
Radiometric Calibration for Internet Photo Collections, Zhipeng Mo, Boxin Shi, Sai-Kit Yeung, Yasuyuki Matsushita

Image Retrieval

Deep Visual-Semantic Quantization for Efficient Image Retrieval, Yue Cao, Mingsheng Long, Jianmin Wang, Shichen Liu
AMVH: Asymmetric Multi-Valued Hashing. Cheng Da, Shibiao Xu, Kun Ding, Gaofeng Meng, Shiming Xiang, Chunhong Pan
Efficient Diffusion on Region Manifolds: Recovering Small Objects With Compact CNN Representations, Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, Teddy Furon, Ondřej Chum
Spatial-Semantic Image Search by Visual Feature Synthesis, Long Mai, Hailin Jin, Zhe Lin, Chen Fang, Jonathan Brandt, Feng Liu
Deep Sketch Hashing: Fast Free-Hand Sketch-Based Image Retrieval, Li Liu, Fumin Shen, Yuming Shen, Xianglong Liu, Ling Shao
Bayesian Supervised Hashing, Zihao Hu, Junxuan Chen, Hongtao Lu, Tongzhen Zhang
Simultaneous Feature Aggregating and Hashing for Large-Scale Image Search, Thanh-Toan Do, Dang-Khoa Le Tan, Trung T. Pham, Ngai-Man Cheung
Discretely Coding Semantic Rank Orders for Supervised Image Hashing, Li Liu, Ling Shao, Fumin Shen, Mengyang Yu
Asymmetric Feature Maps With Application to Sketch Based Retrieval, Giorgos Tolias, Ondřej Chum
Fried Binary Embedding for High-Dimensional Visual Features, Weixiang Hong, Junsong Yuan, Sreyasee Das Bhattacharjee
Learning Multifunctional Binary Codes for Both Category and Attribute Oriented Retrieval Tasks, Haomiao Liu, Ruiping Wang, Shiguang Shan, Xilin Chen
Kernel Square-Loss Exemplar Machines for Image Retrieval, Rafael S. Rezende, Joaquin Zepeda, Jean Ponce, Francis Bach, Patrick Pérez

Human Analysis

LCR-Net: Localization-Classification-Regression for Human Pose. Gregory Rogez, Philippe Weinzaepfel, Cordelia Schmid
Deep Learning on Lie Groups for Skeleton-Based Action Recognition, Zhiwu Huang, Chengde Wan, Thomas Probst, Luc Van Gool
Coarse-To-Fine Volumetric Prediction for Single-Image 3D Human Pose, Georgios Pavlakos, Xiaowei Zhou, Konstantinos G. Derpanis, Kostas Daniilidis
ArtTrack: Articulated Multi-Person Tracking in the Wild, Eldar Insafutdinov, Mykhaylo Andriluka, Leonid Pishchulin, Siyu Tang, Evgeny Levinkov, Bjoern Andres, Bernt Schiele
Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields, Zhe Cao, Tomas Simon, Shih-En Wei, Yaser Sheikh
Weakly Supervised Action Learning With RNN Based Fine-To-Coarse Modeling, Alexander Richard, Hilde Kuehne, Juergen Gall
Detangling People: Individuating Multiple Close People and Their Body Parts via Region Assembly, Hao Jiang, Kristen Grauman
BigHand2.2M Benchmark: Hand Pose Dataset and State of the Art Analysis, Shanxin Yuan, Qi Ye, Björn Stenger, Siddhant Jain, Tae-Kyun Kim
Towards Accurate Multi-Person Pose Estimation in the Wild, George Papandreou, Tyler Zhu, Nori Kanazawa, Alexander Toshev, Jonathan Tompson, Chris Bregler, Kevin Murphy
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset, João Carreira, Andrew Zisserman
PoseTrack: Joint Multi-Person Pose Estimation and Tracking, Umar Iqbal, Anton Milan, Juergen Gall
Learning From Synthetic Humans, Gül Varol, Javier Romero, Xavier Martin, Naureen Mahmood, Michael J. Black, Ivan Laptev, Cordelia Schmid
Hand Keypoint Detection in Single Images Using Multiview Bootstrapping, Tomas Simon, Hanbyul Joo, Iain Matthews, Yaser Sheikh
On Human Motion Prediction Using Recurrent Neural Networks, Julieta Martinez, Michael J. Black, Javier Romero
Unite the People: Closing the Loop Between 3D and 2D Human Representations, Christoph Lassner, Javier Romero, Martin Kiefel, Federica Bogo, Michael J. Black, Peter V. Gehler
Deep Multitask Architecture for Integrated 2D and 3D Human Sensing, Alin-Ionut Popa, Mihai Zanfir, Cristian Sminchisescu
Recurrent 3D Pose Sequence Machines, Mude Lin, Liang Lin, Xiaodan Liang, Keze Wang, Hui Cheng
Thin-Slicing Network: A Deep Structured Model for Pose Estimation in Videos, Jie Song, Limin Wang, Luc Van Gool, Otmar Hilliges
Lifting From the Deep: Convolutional 3D Pose Estimation From a Single Image, Denis Tome, Chris Russell, Lourdes Agapito
3D Human Pose Estimation = 2D Pose Estimation + Matching, Ching-Hang Chen, Deva Ramanan
Joint Multi-Person Pose Estimation and Semantic Part Segmentation, Fangting Xia, Peng Wang, Xianjie Chen, Alan L. Yuille
Look Into Person: Self-Supervised Structure-Sensitive Learning and a New Benchmark for Human Parsing, Ke Gong, Xiaodan Liang, Dongyu Zhang, Xiaohui Shen, Liang Lin

Face Analysis

Learning Residual Images for Face Attribute Manipulation, Wei Shen, Rujie Liu
Disentangled Representation Learning GAN for Pose-Invariant Face Recognition, Luan Tran, Xi Yin, Xiaoming Liu
Photorealistic Facial Texture Inference Using Deep Neural Networks, Shunsuke Saito, Lingyu Wei, Liwen Hu, Koki Nagano, Hao Li
Synthesizing Normalized Faces From Facial Identity Features, Forrester Cole, David Belanger, Dilip Krishnan, Aaron Sarna, Inbar Mosseri, William T. Freeman
Level Playing Field for Million Scale Face recognition, Aaron Nech, Ira Kemelmacher-Shlizerman
Reliable Crowdsourcing and Deep Locality-Preserving Learning for Expression Recognition in the Wild, Shan Li, Weihong Deng, JunPing Du
DenseReg: Fully Convolutional Dense Shape Regression In-The-Wild, Rıza Alp Güler, George Trigeorgis, Epameinondas Antonakos, Patrick Snape, Stefanos Zafeiriou, Iasonas Kokkinos
Neural Aggregation Network for Video Face Recognition, Jiaolong Yang, Peiran Ren, Dongqing Zhang, Dong Chen, Fang Wen, Hongdong Li, Gang Hua
Pose-Aware Person Recognition, Vijay Kumar, Anoop Namboodiri, Manohar Paluri, C. V. Jawahar
Neural Face Editing With Intrinsic Image Disentangling, Zhixin Shu, Ersin Yumer, Sunil Hadap, Kalyan Sunkavalli, Eli Shechtman, Dimitris Samaras
3D Face Morphable Models “In-The-Wild”, James Booth, Epameinondas Antonakos, Stylianos Ploumpis, George Trigeorgis, Yannis Panagakis, Stefanos Zafeiriou
Parametric T-Spline Face Morphable Model for Detailed Fitting in Shape Subspace, Weilong Peng, Zhiyong Feng, Chao Xu, Yong Su
Learning Detailed Face Reconstruction From a Single Image, Elad Richardson, Matan Sela, Roy Or-El, Ron Kimmel

Object Tracking

Context-Aware Correlation Filter Tracking, Matthias Mueller, Neil Smith, Bernard Ghanem
Template Matching With Deformable Diversity Similarity, Itamar Talmi, Roey Mechrez, Lihi Zelnik-Mano
Large Margin Object Tracking With Circulant Feature Maps, Mengmeng Wang, Yong Liu, Zeyi Huang
Attentional Correlation Filter Network for Adaptive Visual Tracking, Jongwon Choi, Hyung Jin Chang, Sangdoo Yun, Tobias Fischer, Yiannis Demiris, Jin Young Choi
Discriminative Correlation Filter With Channel and Spatial Reliability, Alan Lukežič, Tomáš Vojíř, Luka Čehovin Zajc, Jiří Matas, Matej Kristan
End-To-End Representation Learning for Correlation Filter Based Tracking, Jack Valmadre, Luca Bertinetto, João Henriques, Andrea Vedaldi, Philip H. S. Torr
Robust Visual Tracking Using Oblique Random Forests, Le Zhang, Jagannadan Varadarajan, Ponnuthurai Nagaratnam Suganthan, Narendra Ahuja, Pierre Moulin
ECO: Efficient Convolution Operators for Tracking, Martin Danelljan, Goutam Bhat, Fahad Shahbaz Khan, Michael Felsberg

Machine Learning

Learning From Simulated and Unsupervised Images Through Adversarial Training, Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Joshua Susskind, Wenda Wang, Russell Webb
Densely Connected Convolutional Networks, Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger
Network Dissection: Quantifying Interpretability of Deep Visual Representations, David Bau, Bolei Zhou, Aditya Khosla, Aude Oliva, Antonio Torralba
AGA: Attribute-Guided Augmentation, Mandar Dixit, Roland Kwitt, Marc Niethammer, Nuno Vasconcelos
Kernel Pooling for Convolutional Neural Networks, Yin Cui, Feng Zhou, Jiang Wang, Xiao Liu, Yuanqing Lin, Serge Belongie
Local Binary Convolutional Neural Networks, Felix Juefei-Xu, Vishnu Naresh Boddeti, Marios Savvides
All You Need Is Beyond a Good Init: Exploring Better Solution for Training Extremely Deep Convolutional Neural Networks With Orthonormality and Modulation, Di Xie, Jiang Xiong, Shiliang Pu
Newton-Type Methods for Inference in Higher-Order Markov Random Fields, Hariprasad Kannan, Nikos Komodakis, Nikos Paragios

Multiple View Geometry

A New Rank Constraint on Multi-View Fundamental Matrices, and Its Application to Camera Location Recovery, Soumyadip Sengupta, Tal Amir, Meirav Galun, Tom Goldstein, David W. Jacobs, Amit Singer, Ronen Basri
Efficient Solvers for Minimal Problems by Syzygy-Based Reduction, Viktor Larsson, Kalle Åström, Magnus Oskarsson
A Minimal Solution for Two-View Focal-Length Estimation Using Two Affine Correspondences, Daniel Barath, Tekla Toth, Levente Hajder
A Multi-View Stereo Benchmark With High-Resolution Images and Multi-Camera Videos, Thomas Schöps, Johannes L. Schönberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, Andreas Geiger
A Clever Elimination Strategy for Efficient Minimal Solvers. Zuzana Kukelova, Joe Kileel, Bernd Sturmfels, Tomas Pajdla
An Efficient Algebraic Solution to the Perspective-Three-Point Problem, Tong Ke, Stergios I. Roumeliotis
The Misty Three Point Algorithm for Relative Pose, Tobias Palmér, Kalle Åström, Jan-Michael Frahm
Consensus Maximization With Linear Matrix Inequality Constraints, Pablo Speciale, Danda Pani Paudel, Martin R. Oswald, Till Kroeger, Luc Van Gool, Marc Pollefeys

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