1 citations · 2 across the 5 of their papers we have counts for
7 papers · 1 filter
MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth Estimation
Ansh Shah, K Madhava Krishna
Recovering metric depth from a single image remains a fundamental challenge in computer vision, requiring both scene understanding and accurate scaling. While deep learning has adv…
DIFFNAT: Improving Diffusion Image Quality Using Natural Image Statistics
Aniket Roy, Maiterya Suin, Anshul Shah +3
Diffusion models have advanced generative AI significantly in terms of editing and creating naturalistic images. However, efficiently improving generated image quality is still of…
GaitContour: Efficient Gait Recognition based on a Contour-Pose Representation
Yuxiang Guo, Anshul Shah, Jiang Liu +3
Gait recognition holds the promise to robustly identify subjects based on walking patterns instead of appearance information. In recent years, this field has been dominated by lear…
HaLP: Hallucinating Latent Positives for Skeleton-based Self-Supervised Learning of Actions
Anshul Shah, Aniket Roy, Ketul Shah +4
Supervised learning of skeleton sequence encoders for action recognition has received significant attention in recent times. However, learning such encoders without labels continue…
Unfolding a blurred image
Kuldeep Purohit, Anshul Shah, A. N. Rajagopalan
We present a solution for the goal of extracting a video from a single motion blurred image to sequentially reconstruct the clear views of a scene as beheld by the camera during th…
Pose And Joint-Aware Action Recognition
Anshul Shah, Shlok Mishra, Ankan Bansal +3
Recent progress on action recognition has mainly focused on RGB and optical flow features. In this paper, we approach the problem of joint-based action recognition. Unlike other mo…