activity
20162026
most citedOn the Opportunities and Risks of Foundation Models

2.3k citations · 8.5k across the 156 of their papers we have counts for

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Showing 2024 · cs.CVShow all

6 papers · 2 filters

cs.CV2024★ 1 cited

BEHAVIOR Vision Suite: Customizable Dataset Generation via Simulation

Yunhao Ge, Yihe Tang, Jiashu Xu +20

The systematic evaluation and understanding of computer vision models under varying conditions require large amounts of data with comprehensive and customized labels, which real-wo…

cs.CV2024

3D Congealing: 3D-Aware Image Alignment in the Wild

Yunzhi Zhang, Zizhang Li, Amit Raj +5

We propose 3D Congealing, a novel problem of 3D-aware alignment for 2D images capturing semantically similar objects. Given a collection of unlabeled Internet images, our goal is t…

cs.CV2024

PhysDreamer: Physics-Based Interaction with 3D Objects via Video Generation

Tianyuan Zhang, Hong-Xing Yu, Rundi Wu +5

Realistic object interactions are crucial for creating immersive virtual experiences, yet synthesizing realistic 3D object dynamics in response to novel interactions remains a sign…

cs.CV2024

Reconstruction and Simulation of Elastic Objects with Spring-Mass 3D Gaussians

Licheng Zhong, Hong-Xing Yu, Jiajun Wu +1

Reconstructing and simulating elastic objects from visual observations is crucial for applications in computer vision and robotics. Existing methods, such as 3D Gaussians, model 3D…

cs.CV2024

Unsupervised Discovery of Object-Centric Neural Fields

Rundong Luo, Hong-Xing Yu, Jiajun Wu

We study inferring 3D object-centric scene representations from a single image. While recent methods have shown potential in unsupervised 3D object discovery from simple synthetic…

cs.CV2024

Learning the 3D Fauna of the Web

Zizhang Li, Dor Litvak, Ruining Li +6

Learning 3D models of all animals on the Earth requires massively scaling up existing solutions. With this ultimate goal in mind, we develop 3D-Fauna, an approach that learns a pan…