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Pulling The REINS: Training-Free Safety Alignment of Video Diffusion Models via Representation Steering
Rohit Kundu, Arindam Dutta, Sarosij Bose +2
Open-weight video diffusion models can generate photorealistic unsafe content, from violence to misinformation, yet existing defenses either require expensive safety fine-tuning th…
VOccl3D: A Video Benchmark Dataset for 3D Human Pose and Shape Estimation under real Occlusions
Yash Garg, Saketh Bachu, Arindam Dutta +5
Human pose and shape (HPS) estimation methods have been extensively studied, with many demonstrating high zero-shot performance on in-the-wild images and videos. However, these met…
Leveraging Synthetic Adult Datasets for Unsupervised Infant Pose Estimation
Sarosij Bose, Hannah Dela Cruz, Arindam Dutta +3
Human pose estimation is a critical tool across a variety of healthcare applications. Despite significant progress in pose estimation algorithms targeting adults, such developments…
Uncertainty-Aware Diffusion Guided Refinement of 3D Scenes
Sarosij Bose, Arindam Dutta, Sayak Nag +4
Reconstructing 3D scenes from a single image is a fundamentally ill-posed task due to the severely under-constrained nature of the problem. Consequently, when the scene is rendered…
CHROME: Clothed Human Reconstruction with Occlusion-Resilience and Multiview-Consistency from a Single Image
Arindam Dutta, Meng Zheng, Zhongpai Gao +5
Reconstructing clothed humans from a single image is a fundamental task in computer vision with wide-ranging applications. Although existing monocular clothed human reconstruction…
Unsupervised Domain Adaptation for Occlusion Resilient Human Pose Estimation
Arindam Dutta, Sarosij Bose, Saketh Bachu +3
Occlusions are a significant challenge to human pose estimation algorithms, often resulting in inaccurate and anatomically implausible poses. Although current occlusion-robust huma…