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Jun Liu

9 papers hereh-index 8258 citations17 works total

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

author position
  • middle author4
  • last author5

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.AI2
  • cs.CR1
  • cs.GR1
  • cs.LG1
same name
  • Jun Liu — 17 papers, h 5
  • Jun Liu — 17 papers, h 8
  • Jun Liu — 15 papers, h 7
  • Jun Liu — 13 papers, h 8
  • Jun Liu — 9 papers, h 3
  • Jun Liu — 9 papers, h 7

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
collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Boot-and-Feedback Framework for Generalist-Expert Model Collaboration in Breast Ultrasound Diagnosis

Ming Cheng, Hongyu Sun, Zhaolin Chen +3

Breast ultrasound (BUS) is widely used for breast cancer diagnosis yet remains operator-dependent. While deep learning shows promise, ensuring diagnostic reliability and interpreta…

cs.CV2026

Sports-QA: A Large-Scale Video Question Answering Benchmark for Complex and Professional Sports

Haopeng Li, Andong Deng, Jun Liu +5

Reasoning over sports videos for question answering is an important task with numerous applications, such as player training and information retrieval. However, this task has not b…

cs.CV2025

GaussianBlock: Building Part-Aware Compositional and Editable 3D Scene by Primitives and Gaussians

Shuyi Jiang, Qihao Zhao, Hossein Rahmani +3

Recently, with the development of Neural Radiance Fields and Gaussian Splatting, 3D reconstruction techniques have achieved remarkably high fidelity. However, the latent representa…

cs.CV2025

Avatar Concept Slider: Controllable Editing of Concepts in 3D Human Avatars

Lin Geng Foo, Yixuan He, Ajmal Saeed Mian +3

Text-based editing of 3D human avatars to precisely match user requirements is challenging due to the inherent ambiguity and limited expressiveness of natural language. To overcome…

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