Papers
WCP: Worst-Case Perturbations for Semi-Supervised Deep Learning
Liheng Zhang, Guo-Jun Qi
Weakly-Supervised 3D Human Pose Learning via Multi-View Images in the Wild
Umar Iqbal, Pavlo Molchanov, Jan Kautz
Weakly-Supervised Action Localization by Generative Attention Modeling
Baifeng Shi, Qi Dai, Yadong Mu et al.
Weakly Supervised Discriminative Feature Learning With State Information for Person Identification
Hong-Xing Yu, Wei-Shi Zheng
Weakly-Supervised Domain Adaptation via GAN and Mesh Model for Estimating 3D Hand Poses Interacting Objects
Seungryul Baek, Kwang In Kim, Tae-Kyun Kim
Weakly Supervised Fine-Grained Image Classification via Guassian Mixture Model Oriented Discriminative Learning
Zhihui Wang, Shijie Wang, Shuhui Yang et al.
Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild
Dominik Kulon, Riza Alp Guler, Iasonas Kokkinos et al.
Weakly-Supervised Salient Object Detection via Scribble Annotations
Jing Zhang, Xin Yu, Aixuan Li et al.
Weakly Supervised Semantic Point Cloud Segmentation: Towards 10x Fewer Labels
Xun Xu, Gim Hee Lee
Weakly-Supervised Semantic Segmentation via Sub-Category Exploration
Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung et al.
Weakly Supervised Visual Semantic Parsing
Alireza Zareian, Svebor Karaman, Shih-Fu Chang
Webly Supervised Knowledge Embedding Model for Visual Reasoning
Wenbo Zheng, Lan Yan, Chao Gou et al.
What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation
Jiahua Dong, Yang Cong, Gan Sun et al.
What Deep CNNs Benefit From Global Covariance Pooling: An Optimization Perspective
Qilong Wang, Li Zhang, Banggu Wu et al.
What Does Plate Glass Reveal About Camera Calibration?
Qian Zheng, Jinnan Chen, Zhan Lu et al.
What It Thinks Is Important Is Important: Robustness Transfers Through Input Gradients
Alvin Chan, Yi Tay, Yew-Soon Ong
What Machines See Is Not What They Get: Fooling Scene Text Recognition Models With Adversarial Text Images
Xing Xu, Jiefu Chen, Jinhui Xiao et al.
What Makes Training Multi-Modal Classification Networks Hard?
Weiyao Wang, Du Tran, Matt Feiszli
What's Hidden in a Randomly Weighted Neural Network?
Vivek Ramanujan, Mitchell Wortsman, Aniruddha Kembhavi et al.
What You See is What You Get: Exploiting Visibility for 3D Object Detection
Peiyun Hu, Jason Ziglar, David Held et al.
When2com: Multi-Agent Perception via Communication Graph Grouping
Yen-Cheng Liu, Junjiao Tian, Nathaniel Glaser et al.
When NAS Meets Robustness: In Search of Robust Architectures Against Adversarial Attacks
Minghao Guo, Yuzhe Yang, Rui Xu et al.
When to Use Convolutional Neural Networks for Inverse Problems
Nathaniel Chodosh, Simon Lucey
Where Am I Looking At? Joint Location and Orientation Estimation by Cross-View Matching
Yujiao Shi, Xin Yu, Dylan Campbell et al.
Where Does It End? - Reasoning About Hidden Surfaces by Object Intersection Constraints
Michael Strecke, Jorg Stuckler