activity
20182024
most citedUnsupervised Semantic Segmentation by Distilling Feature Correspondences

115 citations · 238 across the 7 of their papers we have counts for

collaborators

10 papers

cs.CV2022115 cited

Unsupervised Semantic Segmentation by Distilling Feature Correspondences

Mark Hamilton, Zhoutong Zhang, Bharath Hariharan +2

Unsupervised semantic segmentation aims to discover and localize semantically meaningful categories within image corpora without any form of annotation. To solve this task, algorit…

cs.GR20212 cited

Differentiable Surface Rendering via Non-Differentiable Sampling

Forrester Cole, Kyle Genova, Avneesh Sud +2

We present a method for differentiable rendering of 3D surfaces that supports both explicit and implicit representations, provides derivatives at occlusion boundaries, and is fast…

cs.CV202126 cited

Consistent Depth of Moving Objects in Video

Zhoutong Zhang, Forrester Cole, Richard Tucker +2

We present a method to estimate depth of a dynamic scene, containing arbitrary moving objects, from an ordinary video captured with a moving camera. We seek a geometrically and tem…

cs.CV20215 cited

Editing Conditional Radiance Fields

Steven Liu, Xiuming Zhang, Zhoutong Zhang +3

A neural radiance field (NeRF) is a scene model supporting high-quality view synthesis, optimized per scene. In this paper, we explore enabling user editing of a category-level NeR…

cs.CV20201 cited

End-to-End Optimization of Scene Layout

Andrew Luo, Zhoutong Zhang, Jiajun Wu +1

We propose an end-to-end variational generative model for scene layout synthesis conditioned on scene graphs. Unlike unconditional scene layout generation, we use scene graphs as a…

cs.CV201880 cited

Learning to Reconstruct Shapes from Unseen Classes

Xiuming Zhang, Zhoutong Zhang, Chengkai Zhang +3

From a single image, humans are able to perceive the full 3D shape of an object by exploiting learned shape priors from everyday life. Contemporary single-image 3D reconstruction a…