7 citations · 8 across the 4 of their papers we have counts for
4 papers
PARC: A Quantitative Framework Uncovering the Symmetries within Vision Language Models
Jenny Schmalfuss, Nadine Chang, Vibashan VS +3
Vision language models (VLMs) respond to user-crafted text prompts and visual inputs, and are applied to numerous real-world problems. VLMs integrate visual modalities with large l…
FaceXBench: Evaluating Multimodal LLMs on Face Understanding
Kartik Narayan, Vibashan VS, Vishal M. Patel
Multimodal Large Language Models (MLLMs) demonstrate impressive problem-solving abilities across a wide range of tasks and domains. However, their capacity for face understanding h…
Towards Online Domain Adaptive Object Detection
Vibashan VS, Poojan Oza, Vishal M. Patel
Existing object detection models assume both the training and test data are sampled from the same source domain. This assumption does not hold true when these detectors are deploye…
Instance Relation Graph Guided Source-Free Domain Adaptive Object Detection
Vibashan VS, Poojan Oza, Vishal M. Patel
Unsupervised Domain Adaptation (UDA) is an effective approach to tackle the issue of domain shift. Specifically, UDA methods try to align the source and target representations to i…