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20162021
most citedRemoval of Batch Effects using Generative Adversarial Networks

2 citations · 2 across the 1 of their papers we have counts for

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cs.CV2021

Gravity-Aware Monocular 3D Human-Object Reconstruction

Rishabh Dabral, Soshi Shimada, Arjun Jain +2

This paper proposes GraviCap, i.e., a new approach for joint markerless 3D human motion capture and object trajectory estimation from monocular RGB videos. We focus on scenes with…

cs.CV2019

Multi-Person 3D Human Pose Estimation from Monocular Images

Rishabh Dabral, Nitesh B Gundavarapu, Rahul Mitra +3

Multi-person 3D human pose estimation from a single image is a challenging problem, especially for in-the-wild settings due to the lack of 3D annotated data. We propose HG-RCNN, a…

cs.CV2019

ProtoGAN: Towards Few Shot Learning for Action Recognition

Sai Kumar Dwivedi, Vikram Gupta, Rahul Mitra +2

Few-shot learning (FSL) for action recognition is a challenging task of recognizing novel action categories which are represented by few instances in the training data. In a more g…

cs.CV2019

Progression Modelling for Online and Early Gesture Detection

Vikram Gupta, Sai Kumar Dwivedi, Rishabh Dabral +1

Online and Early detection of gestures is crucial for building touchless gesture based interfaces. These interfaces should operate on a stream of video frames instead of the comple…

cs.CV2019

Multiview-Consistent Semi-Supervised Learning for 3D Human Pose Estimation

Rahul Mitra, Nitesh B. Gundavarapu, Abhishek Sharma +1

The best performing methods for 3D human pose estimation from monocular images require large amounts of in-the-wild 2D and controlled 3D pose annotated datasets which are costly an…

cs.CV2019

Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking

Saurabh Sharma, Pavan Teja Varigonda, Prashast Bindal +2

Monocular 3D human-pose estimation from static images is a challenging problem, due to the curse of dimensionality and the ill-posed nature of lifting 2D-to-3D. In this paper, we p…