46 citations · 196 across the 34 of their papers we have counts for
6 papers · 1 filter
Efficient Geometry-aware 3D Generative Adversarial Networks
Eric R. Chan, Connor Z. Lin, Matthew A. Chan +9
Unsupervised generation of high-quality multi-view-consistent images and 3D shapes using only collections of single-view 2D photographs has been a long-standing challenge. Existing…
Self-Supervised Object Detection via Generative Image Synthesis
Siva Karthik Mustikovela, Shalini De Mello, Aayush Prakash +5
We present SSOD, the first end-to-end analysis-by synthesis framework with controllable GANs for the task of self-supervised object detection. We use collections of real world imag…
Learning Contrastive Representation for Semantic Correspondence
Taihong Xiao, Sifei Liu, Shalini De Mello +3
Dense correspondence across semantically related images has been extensively studied, but still faces two challenges: 1) large variations in appearance, scale and pose exist even f…
Weakly-Supervised Physically Unconstrained Gaze Estimation
Rakshit Kothari, Shalini De Mello, Umar Iqbal +3
A major challenge for physically unconstrained gaze estimation is acquiring training data with 3D gaze annotations for in-the-wild and outdoor scenarios. In contrast, videos of hum…
Contrastive Syn-to-Real Generalization
Wuyang Chen, Zhiding Yu, Shalini De Mello +4
Training on synthetic data can be beneficial for label or data-scarce scenarios. However, synthetically trained models often suffer from poor generalization in real domains due to…
Learning to Track Instances without Video Annotations
Yang Fu, Sifei Liu, Umar Iqbal +3
Tracking segmentation masks of multiple instances has been intensively studied, but still faces two fundamental challenges: 1) the requirement of large-scale, frame-wise annotation…