4 papers
WorldBench: Benchmarking Physical Understanding of World Models by Isolating Physics Concepts
Rishi Upadhyay, Howard Zhang, Jim Solomon +7
Recent advances in generative foundational models, often termed "world models," have propelled interest in applying them to critical tasks like robotic planning and autonomous syst…
PromptGAR: Flexible Promptive Group Activity Recognition
Zhangyu Jin, Andrew Feng, Ankur Chemburkar +1
We present PromptGAR, a novel framework for Group Activity Recognition (GAR) that offering both input flexibility and high recognition accuracy. The existing approaches suffer from…
SHARDeg: A Benchmark for Skeletal Human Action Recognition in Degraded Scenarios
Simon Malzard, Nitish Mital, Richard Walters +3
Computer vision (CV) models for detection, prediction or classification tasks operate on video data-streams that are often degraded in the real world, due to deployment in real-tim…
Improving Object Detection by Modifying Synthetic Data with Explainable AI
Nitish Mital, Simon Malzard, Richard Walters +3
Limited real-world data severely impacts model performance in many computer vision domains, particularly for samples that are underrepresented in training. Synthetically generated…