32:00
PR-300: Self-Supervised Co-Training for Video Representation Learning
34:14
PR-287: Quantifying Behaviour of CNNs and Humans by Measuring Error Consistency
40:53
PR-277: Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
30:41
PR-260: Momentum Contrast for Unsupervised Visual Representation Learning
31:59
PR-244: Semantic Pyramid for Image Generation
29:04
PR-234: Zero-Shot Super-Resolution using Deep Internal Learning
29:39
PR-220: Learning Correspondence from the Cycle-Consistency of Time
31:35
PR-205: A Closer Look at Few Shot Classification
26:59
PR-192: MoCoGAN: Decomposing Motion and Content for Video Generation
26:45
PR-178: Graph Convolutional Network
32:36
PR-163: CNN Attention Networks
25:14
PR-150: ImageNet-trained CNNs are Biased Towards Textures
27:34
PR-139: Fully Convolutional Siamese Networks for Object Tracking
29:57
PR-127: FaceNet
29:22
PR-113: The Perception Distortion Tradeoff
33:06
PR-103: Visualizing Data using t-SNE
26:42
PR-096: Taskonomy: Disentangling Task Transfer Learning
26:13
PR-083: Non-local Neural Networks
22:54
PR-072: Deep Compression
21:41
PR-057: Mask R-CNN
37:57
PR-045: DeepLab: Semantic Image Segmentation
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Computer Vision Research Scientist
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