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Jiacheng Wei

Nanyang Technological University

22 papers hereh-index 11492 citations25 works total

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

author position
  • first author4
  • middle author15

Across the 19 of 22 papers where every author was matched, so the position is known.

fields
  • cs.CV19
  • cs.RO3
affiliations
  • Nanyang Technological University
same name
  • Jiacheng Wei — 3 papers, h 0
  • Jiacheng Wei — 2 papers, h 2
  • Jiacheng Wei — 1 paper, h 4

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
20202026
most citedMulti-Path Region Mining For Weakly Supervised 3D Semantic Segmentation on Point Clouds

15 citations · 42 across the 19 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.RO2026

IronMind: Scaling Humanoid Dexterous Manipulation via Camera-Space Ego-Centric Pretraining

Huimin Pan, Yufan Ren, Kunpeng Song +16

Egocentric human video offers a scalable data source for dexterous manipulation, yet using it to train humanoid robots presents two challenges: (1) an embodiment gap, as human hand…

cs.RO2026

XPACE: Joint World and Action Modeling from Heterogeneous Experience

Jiacheng Wei, Jerry Bai, Xiaoyu Yue +13

A general-purpose robot needs to draw on diverse experience, choose actions, and anticipate how those actions will change the world. We introduce XPACE, a unified embodied world mo…

cs.RO2026

AnyWorld: Factorized Egocentric World Models for Cross-Embodiment Generalization

Cheng Chen, Jerry Bai, Jiacheng Wei +11

Collecting contact-rich robot experiences at scale remains a major bottleneck for generalizable manipulation. Beyond data quantity, robot learning also requires diverse experiences…

cs.CV2026

EditVerse3D: High-Quality 3D Object Editing with Region-Aware Learning

Youtan Yin, Yanning Zhou, Jiacheng Wei +6

Local editing of 3D objects remains a long-standing challenge. When interacting with 3D content, humans naturally tend to specify a coarse region of interest for modification rathe…

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