6 papers
Thermo-VL: Extending Vision-Language Models to Thermal Infrared Perception
Rusiru Thushara, Yasiru Ranasinghe, Jay Paranjape +1
Vision-language models (VLMs) often fail under low illumination because their visual grounding is learned predominantly from RGB imagery, whereas thermal infrared preserves complem…
Referring Change Detection in Remote Sensing Imagery
Yilmaz Korkmaz, Jay N. Paranjape, Celso M. de Melo +1
Change detection in remote sensing imagery is essential for applications such as urban planning, environmental monitoring, and disaster management. Traditional change detection met…
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…
GenDeg: Diffusion-based Degradation Synthesis for Generalizable All-In-One Image Restoration
Sudarshan Rajagopalan, Nithin Gopalakrishnan Nair, Jay N. Paranjape +1
Deep learning-based models for All-In-One Image Restoration (AIOR) have achieved significant advancements in recent years. However, their practical applicability is limited by poor…
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…