2 citations · 2 across the 7 of their papers we have counts for
6 papers · 1 filter
When Trackers Fail: VLM-Guided Verification and Recovery for Robust Video Object Segmentation
Valay Bundele, Susmit Agrawal, Mehran Hosseinzadeh +2
Recent trackers built on foundation models such as the Segment Anything Model (SAM) achieve strong performance by propagating object masks through memory. However, this strength is…
ReMeDI: Refined Memory for Disambiguation of Identities with SAM3 in Surgical Segmentation
Valay Bundele, Mehran Hosseinzadeh, Hendrik P. A. Lensch
Accurate surgical instrument segmentation in endoscopy is crucial for computer-assisted interventions, yet remains challenging due to frequent occlusions, rapid motion, and long-te…
You Are Your Best Teacher: Semi-Supervised Surgical Point Tracking with Cycle-Consistent Self-Distillation
Valay Bundele, Mehran Hosseinzadeh, Hendrik Lensch
Synthetic datasets have enabled significant progress in point tracking by providing large-scale, densely annotated supervision. However, deploying these models in real-world domain…
Evaluating Self-Supervised Learning in Medical Imaging: A Benchmark for Robustness, Generalizability, and Multi-Domain Impact
Valay Bundele, Karahan Sarıtaş, Bora Kargi +4
Self-supervised learning (SSL) has emerged as a promising paradigm in medical imaging, addressing the chronic challenge of limited labeled data in healthcare settings. While SSL ha…
Scaling Vision-and-Language Navigation With Offline RL
Valay Bundele, Mahesh Bhupati, Biplab Banerjee +1
The study of vision-and-language navigation (VLN) has typically relied on expert trajectories, which may not always be available in real-world situations due to the significant eff…
Learning Class and Domain Augmentations for Single-Source Open-Domain Generalization
Prathmesh Bele, Valay Bundele, Avigyan Bhattacharya +3
Single-source open-domain generalization (SS-ODG) addresses the challenge of labeled source domains with supervision during training and unlabeled novel target domains during testi…