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20162023
most citedUnsupervised Semantic Segmentation by Distilling Feature Correspondences

115 citations · 221 across the 14 of their papers we have counts for

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Showing 2022 · cs.CVShow all

8 papers · 2 filters

cs.CV2022★ 2 cited

Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs

Youya Xia, Josephine Monica, Wei-Lun Chao +3

A self-driving car must be able to reliably handle adverse weather conditions (e.g., snowy) to operate safely. In this paper, we investigate the idea of turning sensor inputs (i.e.…

cs.CV2022★ 2 cited

Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions

Carlos A. Diaz-Ruiz, Youya Xia, Yurong You +11

Advances in perception for self-driving cars have accelerated in recent years due to the availability of large-scale datasets, typically collected at specific locations and under n…

cs.CV2022

Diagnosing and Remedying Shot Sensitivity with Cosine Few-Shot Learners

Davis Wertheimer, Luming Tang, Bharath Hariharan

Few-shot recognition involves training an image classifier to distinguish novel concepts at test time using few examples (shot). Existing approaches generally assume that the shot…

cs.CV2022

Learning to Detect Mobile Objects from LiDAR Scans Without Labels

Yurong You, Katie Z Luo, Cheng Perng Phoo +5

Current 3D object detectors for autonomous driving are almost entirely trained on human-annotated data. Although of high quality, the generation of such data is laborious and costl…

cs.CV2022★ 5 cited

Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception

Yurong You, Katie Z Luo, Xiangyu Chen +6

Self-driving cars must detect vehicles, pedestrians, and other traffic participants accurately to operate safely. Small, far-away, or highly occluded objects are particularly chall…

cs.CV2022★ 115 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…