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20232026
most citedQuickSRNet: Plain Single-Image Super-Resolution Architecture for Faster Inference on Mobile Platforms

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cs.CV2026

On Locality and Length Generalization in Visual Reasoning

Pulkit Madan, Sanjay Haresh, Reza Ebrahimi +3

A striking feature of the human visual system is that it ingests visual information through a series of local foveated glimpses, rather than a single global computation. This makes…

cs.CV2025

Can Multi-Modal LLMs Provide Live Step-by-Step Task Guidance?

Apratim Bhattacharyya, Bicheng Xu, Sanjay Haresh +6

Multi-modal Large Language Models (LLM) have advanced conversational abilities but struggle with providing live, interactive step-by-step guidance, a key capability for future AI a…

cs.CV2025

Can Vision-Language Models Answer Face to Face Questions in the Real-World?

Reza Pourreza, Rishit Dagli, Apratim Bhattacharyya +3

AI models have made significant strides in recent years in their ability to describe and answer questions about real-world images. They have also made progress in the ability to co…

cs.CV2024

What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction

Sunny Panchal, Apratim Bhattacharyya, Guillaume Berger +10

Vision-language models have shown impressive progress in recent years. However, existing models are largely limited to turn-based interactions, where each turn must be stepped (i.e…

cs.CV2023

Painter: Teaching Auto-regressive Language Models to Draw Sketches

Reza Pourreza, Apratim Bhattacharyya, Sunny Panchal +3

Large language models (LLMs) have made tremendous progress in natural language understanding and they have also been successfully adopted in other domains such as computer vision,…

cs.CV2023

Look, Remember and Reason: Grounded reasoning in videos with language models

Apratim Bhattacharyya, Sunny Panchal, Mingu Lee +3

Multi-modal language models (LM) have recently shown promising performance in high-level reasoning tasks on videos. However, existing methods still fall short in tasks like causal…

cs.CV2023

Is end-to-end learning enough for fitness activity recognition?

Antoine Mercier, Guillaume Berger, Sunny Panchal +5

End-to-end learning has taken hold of many computer vision tasks, in particular, related to still images, with task-specific optimization yielding very strong performance. Neverthe…