4 citations · 5 across the 8 of their papers we have counts for
8 papers · 1 filter
World-Coherent Decoding: Self-Verifying Test-Time Planning for World Action Models
Chuhan Zhang, Seiji Ito, Kenta Hoshino +2
World Action Models (WAMs) aim to control robots by stochastically generating visual futures and then decoding actions, but empirical observations indicate that the results can str…
Video Generation Models are General-Purpose Vision Learners
Letian Wang, Chuhan Zhang, Rishabh Kabra +9
Driven by next-token prediction, NLP shifted from task-specific models into powerful generalist foundation models. What, then, is the equivalent catalyst needed to achieve a genera…
Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Ratings
Olivia Wiles, Chuhan Zhang, Isabela Albuquerque +11
While text-to-image (T2I) generative models have become ubiquitous, they do not necessarily generate images that align with a given prompt. While previous work has evaluated T2I al…
Helping Hands: An Object-Aware Ego-Centric Video Recognition Model
Chuhan Zhang, Ankush Gupta, Andrew Zisserman
We introduce an object-aware decoder for improving the performance of spatio-temporal representations on ego-centric videos. The key idea is to enhance object-awareness during trai…
Making the Most of What You Have: Adapting Pre-trained Visual Language Models in the Low-data Regime
Chuhan Zhang, Antoine Miech, Jiajun Shen +2
Large-scale visual language models are widely used as pre-trained models and then adapted for various downstream tasks. While humans are known to efficiently learn new tasks from a…
Is an Object-Centric Video Representation Beneficial for Transfer?
Chuhan Zhang, Ankush Gupta, Andrew Zisserman
The objective of this work is to learn an object-centric video representation, with the aim of improving transferability to novel tasks, i.e., tasks different from the pre-training…
Temporal Query Networks for Fine-grained Video Understanding
Chuhan Zhang, Ankush Gupta, Andrew Zisserman
Our objective in this work is fine-grained classification of actions in untrimmed videos, where the actions may be temporally extended or may span only a few frames of the video. W…
Adaptive Text Recognition through Visual Matching
Chuhan Zhang, Ankush Gupta, Andrew Zisserman
In this work, our objective is to address the problems of generalization and flexibility for text recognition in documents. We introduce a new model that exploits the repetitive na…