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Ye Shi

48 papers hereh-index 17958 citations51 works total

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

author position
  • middle author27
  • last author17

Across the 44 of 48 papers where every author was matched, so the position is known.

fields
  • cs.CV24
  • cs.RO12
  • cs.LG10
  • cs.AI1
  • cs.HC1
same name
  • Ye Shi — 8 papers, h 3
  • Ye Shi — 8 papers, h 2
  • Ye Shi — 7 papers, h 7
  • Ye Shi — 5 papers, h 8
  • Ye Shi — 3 papers, h 3
  • Ye Shi — 3 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
20222026
most citedUnified Optimal Transport Framework for Universal Domain Adaptation

24 citations · 47 across the 39 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022★ 3 cited

NeuralDome: A Neural Modeling Pipeline on Multi-View Human-Object Interactions

Juze Zhang, Haimin Luo, Hongdi Yang +6

Humans constantly interact with objects in daily life tasks. Capturing such processes and subsequently conducting visual inferences from a fixed viewpoint suffers from occlusions,…

cs.CV2022★ 2 cited

Lifelong Person Re-Identification via Knowledge Refreshing and Consolidation

Chunlin Yu, Ye Shi, Zimo Liu +2

Lifelong person re-identification (LReID) is in significant demand for real-world development as a large amount of ReID data is captured from diverse locations over time and cannot…

cs.LG2022

Knowledge-Aware Federated Active Learning with Non-IID Data

Yu-Tong Cao, Ye Shi, Baosheng Yu +2

Federated learning enables multiple decentralized clients to learn collaboratively without sharing the local training data. However, the expensive annotation cost to acquire data l…

cs.CV2022★ 24 cited

Unified Optimal Transport Framework for Universal Domain Adaptation

Wanxing Chang, Ye Shi, Hoang Duong Tuan +1

Universal Domain Adaptation (UniDA) aims to transfer knowledge from a source domain to a target domain without any constraints on label sets. Since both domains may hold private cl…

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