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Mengya Liu

4 papers hereh-index 216 citations6 works total

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

author position
  • first author3
  • middle author1

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

fields
  • cs.CV3
  • cs.RO1
same name
  • Mengya Liu — 3 papers, h 3
  • Mengya Liu — 2 papers, h 1
  • Mengya Liu — 1 paper, h 7
  • Mengya Liu — 1 paper, h 9
  • Mengya Liu — 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
20242026
most citedSelf-supervised Shape Completion via Involution and Implicit Correspondences

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2026

LARA: Latent Action Representation Alignment for Vision-Language-Action Models

Mengya Liu, Baoxiong Jia, Jiangyong Huang +2

Visual-language action (VLA) models enable robots to predict actions directly from observations and language instructions, but their performance depends on large-scale, high-qualit…

cs.RO2026

OmniClone: Engineering a Robust, All-Rounder Whole-Body Humanoid Teleoperation System

Yixuan Li, Le Ma, Yutang Lin +8

Whole-body humanoid teleoperation enables humans to remotely control humanoid robots, serving as both a real-time operational tool and a scalable engine for collecting demonstratio…

cs.CV2025

One2Any: One-Reference 6D Pose Estimation for Any Object

Mengya Liu, Siyuan Li, Ajad Chhatkuli +3

6D object pose estimation remains challenging for many applications due to dependencies on complete 3D models, multi-view images, or training limited to specific object categories.…

cs.CV2024★ 1 cited

Self-supervised Shape Completion via Involution and Implicit Correspondences

Mengya Liu, Ajad Chhatkuli, Janis Postels +2

3D shape completion is traditionally solved using supervised training or by distribution learning on complete shape examples. Recently self-supervised learning approaches that do n…

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