activity
20182023
most citedUnsupervised Semantic Segmentation by Distilling Feature Correspondences

115 citations · 127 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

20 papers · 1 filter

cs.CV2023

Unsupervised Domain Adaptation for Self-Driving from Past Traversal Features

Travis Zhang, Katie Luo, Cheng Perng Phoo +5

The rapid development of 3D object detection systems for self-driving cars has significantly improved accuracy. However, these systems struggle to generalize across diverse driving…

cs.CV2023

Doppelgangers: Learning to Disambiguate Images of Similar Structures

Ruojin Cai, Joseph Tung, Qianqian Wang +3

We consider the visual disambiguation task of determining whether a pair of visually similar images depict the same or distinct 3D surfaces (e.g., the same or opposite sides of a s…

cs.CV2023

RealFill: Reference-Driven Generation for Authentic Image Completion

Luming Tang, Nataniel Ruiz, Qinghao Chu +8

Recent advances in generative imagery have brought forth outpainting and inpainting models that can produce high-quality, plausible image content in unknown regions. However, the c…

cs.CV2023

Tracking Everything Everywhere All at Once

Qianqian Wang, Yen-Yu Chang, Ruojin Cai +4

We present a new test-time optimization method for estimating dense and long-range motion from a video sequence. Prior optical flow or particle video tracking algorithms typically…

cs.CV2023

Emergent Correspondence from Image Diffusion

Luming Tang, Menglin Jia, Qianqian Wang +2

Finding correspondences between images is a fundamental problem in computer vision. In this paper, we show that correspondence emerges in image diffusion models without any explici…

cs.CV2023

Distilling from Similar Tasks for Transfer Learning on a Budget

Kenneth Borup, Cheng Perng Phoo, Bharath Hariharan

We address the challenge of getting efficient yet accurate recognition systems with limited labels. While recognition models improve with model size and amount of data, many specia…