activity
20232026
collaborators

9 papers

cs.CV2026

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…

cs.CV2026

Gen2Balance: Generative Balancing for Long-Tailed Video Action Recognition

Prajwal Gatti, Simon Jenni, Fabian Caba Heilbron +1

We address the problem of training on long-tailed data for video action recognition. We propose to augment the training set using a text-to-video generative model, conditioned on d…

cs.CV2026

The Indra Representation Hypothesis for Multimodal Alignment

Jianglin Lu, Hailing Wang, Kuo Yang +3

Recent studies have uncovered an interesting phenomenon: unimodal foundation models tend to learn convergent representations, regardless of differences in architecture, training ob…

cs.CV2026

Seeing Through Words: Controlling Visual Retrieval Quality with Language Models

Jianglin Lu, Simon Jenni, Kushal Kafle +3

Text-to-image retrieval is a fundamental task in vision-language learning, yet in real-world scenarios it is often challenged by short and underspecified user queries. Such queries…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2024

Sync from the Sea: Retrieving Alignable Videos from Large-Scale Datasets

Ishan Rajendrakumar Dave, Fabian Caba Heilbron, Mubarak Shah +1

Temporal video alignment aims to synchronize the key events like object interactions or action phase transitions in two videos. Such methods could benefit various video editing, pr…

cs.CV2024

Concept Weaver: Enabling Multi-Concept Fusion in Text-to-Image Models

Gihyun Kwon, Simon Jenni, Dingzeyu Li +3

While there has been significant progress in customizing text-to-image generation models, generating images that combine multiple personalized concepts remains challenging. In this…

cs.CV2023

No More Shortcuts: Realizing the Potential of Temporal Self-Supervision

Ishan Rajendrakumar Dave, Simon Jenni, Mubarak Shah

Self-supervised approaches for video have shown impressive results in video understanding tasks. However, unlike early works that leverage temporal self-supervision, current state-…