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Yuning Chai

17 papers hereh-index 188.6k citations24 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author2
  • middle author12
  • last author1

Across the 16 of 17 papers where every author was matched, so the position is known.

fields
  • cs.CV14
  • cs.LG2
  • cs.RO1
same name
  • Yuning Chai — 7 papers, h 3
  • Yuning Chai — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192023
most citedTNT: Target-driveN Trajectory Prediction

211 citations · 471 across the 13 of their papers we have counts for

collaborators
Showing 2019 · cs.CVShow all

4 papers · 2 filters

cs.CV2019

Scalability in Perception for Autonomous Driving: Waymo Open Dataset

Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla +22

The research community has increasing interest in autonomous driving research, despite the resource intensity of obtaining representative real world data. Existing self-driving dat…

cs.CV2019

StarNet: Targeted Computation for Object Detection in Point Clouds

Jiquan Ngiam, Benjamin Caine, Wei Han +10

Detecting objects from LiDAR point clouds is an important component of self-driving car technology as LiDAR provides high resolution spatial information. Previous work on point-clo…

cs.CV2019

Patchwork: A Patch-wise Attention Network for Efficient Object Detection and Segmentation in Video Streams

Yuning Chai

Recent advances in single-frame object detection and segmentation techniques have motivated a wide range of works to extend these methods to process video streams. In this paper, w…

cs.CV2019★ 28 cited

FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation

Paul Voigtlaender, Yuning Chai, Florian Schroff +3

Many of the recent successful methods for video object segmentation (VOS) are overly complicated, heavily rely on fine-tuning on the first frame, and/or are slow, and are hence of…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.