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20182025
most citedVisual Classification via Description from Large Language Models

57 citations · 58 across the 5 of their papers we have counts for

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6 papers · 1 filter

cs.CV2025

CAViAR: Critic-Augmented Video Agentic Reasoning

Sachit Menon, Ahmet Iscen, Arsha Nagrani +3

Video understanding has seen significant progress in recent years, with models' performance on perception from short clips continuing to rise. Yet, multiple recent benchmarks, such…

cs.CV2023

Generating Illustrated Instructions

Sachit Menon, Ishan Misra, Rohit Girdhar

We introduce the new task of generating Illustrated Instructions, i.e., visual instructions customized to a user's needs. We identify desiderata unique to this task, and formalize…

cs.CV20221 cited

Task Bias in Vision-Language Models

Sachit Menon, Ishaan Preetam Chandratreya, Carl Vondrick

Incidental supervision from language has become a popular approach for learning generic visual representations that can be prompted to perform many recognition tasks in computer vi…

cs.CV202257 cited

Visual Classification via Description from Large Language Models

Sachit Menon, Carl Vondrick

Vision-language models (VLMs) such as CLIP have shown promising performance on a variety of recognition tasks using the standard zero-shot classification procedure -- computing sim…

cs.CV2020

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

Sachit Menon, Alexandru Damian, Shijia Hu +2

The primary aim of single-image super-resolution is to construct high-resolution (HR) images from corresponding low-resolution (LR) inputs. In previous approaches, which have gener…

cs.CV2018

New Techniques for Preserving Global Structure and Denoising with Low Information Loss in Single-Image Super-Resolution

Yijie Bei, Alex Damian, Shijia Hu +3

This work identifies and addresses two important technical challenges in single-image super-resolution: (1) how to upsample an image without magnifying noise and (2) how to preserv…