most citedCross-Modal Fusion and Attention Mechanism for Weakly Supervised Video Anomaly Detection

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Open-Set Object Detection By Aligning Known Class Representations

Hiran Sarkar, Vishal Chudasama, Naoyuki Onoe +2

Open-Set Object Detection (OSOD) has emerged as a contemporary research direction to address the detection of unknown objects. Recently, few works have achieved remarkable performa…

cs.CV20242 cited

Cross-Modal Fusion and Attention Mechanism for Weakly Supervised Video Anomaly Detection

Ayush Ghadiya, Purbayan Kar, Vishal Chudasama +1

Recently, weakly supervised video anomaly detection (WS-VAD) has emerged as a contemporary research direction to identify anomaly events like violence and nudity in videos using on…

cs.CV2024

Beyond Few-shot Object Detection: A Detailed Survey

Vishal Chudasama, Hiran Sarkar, Pankaj Wasnik +2

Object detection is a critical field in computer vision focusing on accurately identifying and locating specific objects in images or videos. Traditional methods for object detecti…

cs.CV2024

Fiducial Focus Augmentation for Facial Landmark Detection

Purbayan Kar, Vishal Chudasama, Naoyuki Onoe +2

Deep learning methods have led to significant improvements in the performance on the facial landmark detection (FLD) task. However, detecting landmarks in challenging settings, suc…

cs.CV2023

Revisiting Class Imbalance for End-to-end Semi-Supervised Object Detection

Purbayan Kar, Vishal Chudasama, Naoyuki Onoe +1

Semi-supervised object detection (SSOD) has made significant progress with the development of pseudo-label-based end-to-end methods. However, many of these methods face challenges…