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Yuxi Li

4 papers here

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

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Yuxi Li — 15 papers, h 15
  • Yuxi Li — 8 papers, h 3
  • Yuxi Li — 4 papers
  • Yuxi Li — 3 papers, h 20
  • Yuxi Li — 2 papers, h 0
  • Yuxi Li — 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

most citedDAC: 2D-3D Retrieval with Noisy Labels via Divide-and-Conquer Alignment and Correction

2 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2026

From Pixels to Concepts: Do Segmentation Models Understand What They Segment?

Shuang Liang, Zeqing Wang, Yuxian Li +2

Segmentation is a fundamental vision task underlying numerous downstream applications. Recent promptable segmentation models, such as Segment Anything Model 3 (SAM3), extend segmen…

cs.CV2024★ 2 cited

DAC: 2D-3D Retrieval with Noisy Labels via Divide-and-Conquer Alignment and Correction

Chaofan Gan, Yuanpeng Tu, Yuxi Li +1

With the recent burst of 2D and 3D data, cross-modal retrieval has attracted increasing attention recently. However, manual labeling by non-experts will inevitably introduce corrup…

cs.CV2024

Memory Consistency Guided Divide-and-Conquer Learning for Generalized Category Discovery

Yuanpeng Tu, Zhun Zhong, Yuxi Li +1

Generalized category discovery (GCD) aims at addressing a more realistic and challenging setting of semi-supervised learning, where only part of the category labels are assigned to…

cs.CV2024

Self-supervised Feature Adaptation for 3D Industrial Anomaly Detection

Yuanpeng Tu, Boshen Zhang, Liang Liu +6

Industrial anomaly detection is generally addressed as an unsupervised task that aims at locating defects with only normal training samples. Recently, numerous 2D anomaly detection…

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