3 citations · 3 across the 8 of their papers we have counts for
9 papers
Grounded Human-Attributed Description and Activity Recognition in Videos
Jay N. Paranjape, Jurijs Nazarovs, Rohan Sarkar +5
Understanding characteristics and activities of individuals in complex multi-person environments is crucial for real-world applications. However, existing datasets often simplify t…
StepAL: Step-aware Active Learning for Cataract Surgical Videos
Nisarg A. Shah, Bardia Safaei, Shameema Sikder +2
Active learning (AL) can reduce annotation costs in surgical video analysis while maintaining model performance. However, traditional AL methods, developed for images or short vide…
F-ViTA: Foundation Model Guided Visible to Thermal Translation
Jay N. Paranjape, Celso de Melo, Vishal M. Patel
Thermal imaging is crucial for scene understanding, particularly in low-light and nighttime conditions. However, collecting large thermal datasets is costly and labor-intensive due…
RP-SAM2: Refining Point Prompts for Stable Surgical Instrument Segmentation
Nuren Zhaksylyk, Ibrahim Almakky, Jay Paranjape +4
Accurate surgical instrument segmentation is essential in cataract surgery for tasks such as skill assessment and workflow optimization. However, limited annotated data makes it di…
:~Cataract Surgical Masked Autoencoder (MAE) based Pre-training
Nisarg A. Shah, Wele Gedara Chaminda Bandara, Shameema Skider +2
Automated analysis of surgical videos is crucial for improving surgical training, workflow optimization, and postoperative assessment. We introduce a CSMAE, Masked Autoencoder (MAE…
Federated Black-Box Adaptation for Semantic Segmentation
Jay N. Paranjape, Shameema Sikder, S. Swaroop Vedula +1
Federated Learning (FL) is a form of distributed learning that allows multiple institutions or clients to collaboratively learn a global model to solve a task. This allows the mode…
S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentation
Jay N. Paranjape, Shameema Sikder, S. Swaroop Vedula +1
Medical image segmentation has been traditionally approached by training or fine-tuning the entire model to cater to any new modality or dataset. However, this approach often requi…
A Mamba-based Siamese Network for Remote Sensing Change Detection
Jay N. Paranjape, Celso de Melo, Vishal M. Patel
Change detection in remote sensing images is an essential tool for analyzing a region at different times. It finds varied applications in monitoring environmental changes, man-made…
Blackbox Adaptation for Medical Image Segmentation
Jay N. Paranjape, Shameema Sikder, S. Swaroop Vedula +1
In recent years, various large foundation models have been proposed for image segmentation. There models are often trained on large amounts of data corresponding to general compute…