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Kun Wang

6 papers hereh-index 8215 citations19 works total

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

author position
  • first author1
  • middle author5

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.CL1
  • cs.HC1
same name
  • Kun Wang — 17 papers, h 7
  • Kun Wang — 17 papers, h 11
  • Kun Wang — 15 papers, h 3
  • Kun Wang — 14 papers, h 5
  • Kun Wang — 9 papers, h 6
  • Kun Wang — 9 papers, 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

most citedNeuroPath: Practically Adopting Motor Imagery Decoding through EEG Signals

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

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

ParseFixer: An Agentic Framework for Document Parsing via Selective Multimodal Correction

LeKai Yu, Hao Liu, Kun Wang +4

In this report, we present our third-place solution for the DataMFM Challenge Track 1: Document Parsing. This track requires models to recover structured Markdown documents from do…

cs.CV2026

NTIRE 2026 Challenge on Video Saliency Prediction: Methods and Results

Andrey Moskalenko, Alexey Bryncev, Ivan Kosmynin +40

This paper presents an overview of the NTIRE 2026 Challenge on Video Saliency Prediction. The goal of the challenge participants was to develop automatic saliency map prediction me…

cs.CV2026

ViSAGE @ NTIRE 2026 Challenge on Video Saliency Prediction

Kun Wang, Yupeng Hu, Zhiran Li +3

In this report, we present our champion solution for the NTIRE 2026 Challenge on Video Saliency Prediction held in conjunction with CVPR 2026. To exploit complementary inductive bi…

cs.CV2025

Visual Self-paced Iterative Learning for Unsupervised Temporal Action Localization

Yupeng Hu, Han Jiang, Hao Liu +3

Recently, temporal action localization (TAL) has garnered significant interest in information retrieval community. However, existing supervised/weakly supervised methods are heavil…

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