Sai Kumar Dwivedi

ChatPose integrates large language models to comprehend and reason about 3D human poses from images or textual descriptions, leveraging world knowledge and body language.

HOT tackles the lack of a reliable approach for detecting human-object 2D contact in images by introducing a dataset of 2D contacts and developing a contact detector guided by part-attention, which surpasses all baseline methods.

ProtoGAN framework addresses the challenge of few-shot learning (FSL) for action recognition and generalized FSL by synthesizing additional examples for novel categories using class prototype vectors.

While addressing the challenges of generalized zero-shot action recognition, our novel framework incorporates an out-of-distribution detector to distinguish between seen and unseen action categories, achieving significant improvements over existing methods.

Our simple yet effective multi-task learning framework addresses the issue of online and early gesture detection by modelling the gesture progression along with frame level recognition.