activity
20172024
most citedVisual Forecasting by Imitating Dynamics in Natural Sequences

6 citations · 15 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2023

Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation

William Shen, Ge Yang, Alan Yu +3

Self-supervised and language-supervised image models contain rich knowledge of the world that is important for generalization. Many robotic tasks, however, require a detailed under…

cs.CV20236 cited

Banana: Banach Fixed-Point Network for Pointcloud Segmentation with Inter-Part Equivariance

Congyue Deng, Jiahui Lei, Bokui Shen +2

Equivariance has gained strong interest as a desirable network property that inherently ensures robust generalization. However, when dealing with complex systems such as articulate…

cs.CV20233 cited

NAP: Neural 3D Articulation Prior

Jiahui Lei, Congyue Deng, Bokui Shen +2

We propose Neural 3D Articulation Prior (NAP), the first 3D deep generative model to synthesize 3D articulated object models. Despite the extensive research on generating 3D object…

cs.CV2018

Taskonomy: Disentangling Task Transfer Learning

Amir Zamir, Alexander Sax, William Shen +3

Do visual tasks have a relationship, or are they unrelated? For instance, could having surface normals simplify estimating the depth of an image? Intuition answers these questions…

cs.CV20176 cited

Visual Forecasting by Imitating Dynamics in Natural Sequences

Kuo-Hao Zeng, William B. Shen, De-An Huang +2

We introduce a general framework for visual forecasting, which directly imitates visual sequences without additional supervision. As a result, our model can be applied at several s…