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Zhipeng Cai

5 papers hereh-index 122 citations7 works total

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

author position
  • first author1
  • middle author2
  • last author2

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG1
same name
  • Zhipeng Cai — 11 papers
  • Zhipeng Cai — 6 papers, h 59
  • Zhipeng Cai — 5 papers, h 13
  • Zhipeng Cai — 5 papers, h 5
  • Zhipeng Cai — 3 papers, h 1
  • Zhipeng Cai — 3 papers, h 5

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

collaborators

5 papers

cs.CV2026

Exploring Audio Hallucination in Egocentric Video Understanding

Ashish Seth, Xinhao Mei, Changsheng Zhao +9

Egocentric videos provide a distinctive setting in which sound serves as crucial cues to understand user activities and surroundings, particularly when visual information is unstab…

cs.LG2026

Neural Computers

Mingchen Zhuge, Changsheng Zhao, Haozhe Liu +16

We propose a new frontier: Neural Computers (NCs) that unify computation, memory, and I/O of traditional computers in a learned runtime state. Our long-term goal is the Completely…

cs.CV2026

EgoAVU: Egocentric Audio-Visual Understanding

Ashish Seth, Xinhao Mei, Changsheng Zhao +9

Understanding egocentric videos plays a vital role for embodied intelligence. Recent multi-modal large language models (MLLMs) can accept both visual and audio inputs. However, due…

cs.CV2025

DepthLM: Metric Depth From Vision Language Models

Zhipeng Cai, Ching-Feng Yeh, Hu Xu +7

Vision language models (VLMs) can flexibly address various vision tasks through text interactions. Although successful in semantic understanding, state-of-the-art VLMs including GP…

cs.CV2025

OmniEvent: Unified Event Representation Learning

Weiqi Yan, Chenlu Lin, Youbiao Wang +5

Event cameras have gained increasing popularity in computer vision due to their ultra-high dynamic range and temporal resolution. However, event networks heavily rely on task-speci…

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