160 citations · 192 across the 12 of their papers we have counts for
8 papers · 1 filter
Feature Recovery for Object Understanding After Irreversible Fire Damage
Aditi Tiwari, Sofia Stoica, Savya Khosla +2
Objects in post-fire environments often undergo irreversible physical transformations that change their geometry, material state, and visual appearance. Detecting and identifying t…
ViTAL-X: Video-Text Alignment with Cross-Modal Temporal Edits
Sethuraman T, Savya Khosla, Onkar Kishor Susladkar +6
Video-text models adapted from image-text architectures (e.g., CLIP) frequently exhibit temporal blindness, the inability to perceive fundamental cues like order, direction, and mo…
T-REN: Learning Text-Aligned Region Tokens Improves Dense Vision-Language Alignment and Scalability
Savya Khosla, Sethuraman T, Aryan Chadha +2
Despite recent progress, vision-language encoders struggle with two core limitations: (1) weak alignment between language and dense vision features, which hurts tasks like open-voc…
Stress Tests REVEAL Fragile Temporal and Visual Grounding in Video-Language Models
Sethuraman T, Savya Khosla, Aditi Tiwari +12
Video-Language Models (VidLMs) achieve strong benchmark scores, yet these scores often hide whether models use the video at all. We show that VidLM failures follow two pathways: so…
FRAME: Pre-Training Video Feature Representations via Anticipation and Memory
Sethuraman TV, Savya Khosla, Vignesh Srinivasakumar +5
Dense video prediction tasks, such as object tracking and semantic segmentation, require video encoders that generate temporally consistent, spatially dense features for every fram…
REN: Fast and Efficient Region Encodings from Patch-Based Image Encoders
Savya Khosla, Sethuraman TV, Barnett Lee +2
We introduce the Region Encoder Network (REN), a fast and effective model for generating region-based image representations using point prompts. Recent methods combine class-agnost…