activity
20242026
most citedHow to Spin an Object: First, Get the Shape Right

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Forecasting Motion in the Wild

Neerja Thakkar, Shiry Ginosar, Jacob Walker +3

Visual intelligence requires anticipating the future behavior of agents, yet vision systems lack a general representation for motion and behavior. We propose dense point trajectori…

cs.CV2026

A Mixed Diet Makes DINO An Omnivorous Vision Encoder

Rishabh Kabra, Maks Ovsjanikov, Drew A. Hudson +5

Pre-trained vision encoders like DINOv2 have demonstrated exceptional performance on unimodal tasks. However, we observe that their features are poorly aligned across different vis…

cs.CV2025

Frozen Forecasting: A Unified Evaluation

Jacob C Walker, Pedro Vélez, Luisa Polania Cabrera +7

Forecasting future events is a fundamental capability for general-purpose systems that plan or act across different levels of abstraction. Yet, evaluating whether a forecast is "co…

cs.CV2025

OpenWorldSAM: Extending SAM2 for Universal Image Segmentation with Language Prompts

Shiting Xiao, Rishabh Kabra, Yuhang Li +3

The ability to segment objects based on open-ended language prompts remains a critical challenge, requiring models to ground textual semantics into precise spatial masks while hand…

cs.CV2025

Direct Motion Models for Assessing Generated Videos

Kelsey Allen, Carl Doersch, Guangyao Zhou +9

A current limitation of video generative video models is that they generate plausible looking frames, but poor motion -- an issue that is not well captured by FVD and other popular…

cs.CV2024★ 1 cited

How to Spin an Object: First, Get the Shape Right

Rishabh Kabra, Drew A. Hudson, Sjoerd van Steenkiste +2

Image-to-3D models increasingly rely on hierarchical generation to disentangle geometry and texture. However, the design choices underlying these two-stage models--particularly the…