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20232026
most citedAdvancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler

1 citations · 6 across the 44 of their papers we have counts for

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15 papers · 1 filter

cs.CV2025

HybriDLA: Hybrid Generation for Document Layout Analysis

Yufan Chen, Omar Moured, Ruiping Liu +4

Conventional document layout analysis (DLA) traditionally depends on empirical priors or a fixed set of learnable queries executed in a single forward pass. While sufficient for ea…

cs.CV2025★ 1 cited

RefAtomNet++: Advancing Referring Atomic Video Action Recognition using Multi-Trajectory Semantic Retrieval

Kunyu Peng, Di Wen, Jia Fu +9

Who is being described, where are they, and what are they doing? Referring Atomic Video Action Recognition (RAVAR) answers these questions jointly by grounding a natural-language r…

cs.CV2025

EReLiFM: Evidential Reliability-Aware Residual Flow Meta-Learning for Open-Set Domain Generalization under Noisy Labels

Kunyu Peng, Di Wen, Kailun Yang +9

Open-Set Domain Generalization (OSDG) aims to enable deep learning models to recognize unseen categories in new domains, which is crucial for real-world applications. Label noise h…

cs.CV2025

Situat3DChange: Situated 3D Change Understanding Dataset for Multimodal Large Language Model

Ruiping Liu, Junwei Zheng, Yufan Chen +6

Physical environments and circumstances are fundamentally dynamic, yet current 3D datasets and evaluation benchmarks tend to concentrate on either dynamic scenarios or dynamic situ…

cs.CV2025★ 1 cited

TY-RIST: Tactical YOLO Tricks for Real-time Infrared Small Target Detection

Abdulkarim Atrash, Omar Moured, Yufan Chen +3

Infrared small target detection (IRSTD) is critical for defense and surveillance but remains challenging due to (1) target loss from minimal features, (2) false alarms in cluttered…

cs.AI2025

MICA: Multi-Agent Industrial Coordination Assistant

Di Wen, Kunyu Peng, Junwei Zheng +6

Industrial workflows demand adaptive and trustworthy assistance that can operate under limited computing, connectivity, and strict privacy constraints. In this work, we present MIC…

cs.CV2025★ 1 cited

RoHOI: Robustness Benchmark for Human-Object Interaction Detection

Di Wen, Kunyu Peng, Kailun Yang +7

Human-Object Interaction (HOI) detection is crucial for robot-human assistance, enabling context-aware support. However, models trained on clean datasets degrade in real-world cond…

cs.CV2025

HopaDIFF: Holistic-Partial Aware Fourier Conditioned Diffusion for Referring Human Action Segmentation in Multi-Person Scenarios

Kunyu Peng, Junchao Huang, Xiangsheng Huang +7

Action segmentation is a core challenge in high-level video understanding, aiming to partition untrimmed videos into segments and assign each a label from a predefined action set.…

cs.CV2025★ 1 cited

Go Beyond Earth: Understanding Human Actions and Scenes in Microgravity Environments

Di Wen, Lei Qi, Kunyu Peng +9

Despite substantial progress in video understanding, most existing datasets are limited to Earth's gravitational conditions. However, microgravity alters human motion, interactions…

cs.CV2025

CHAOS: Chart Analysis with Outlier Samples

Omar Moured, Yufan Chen, Ruiping Liu +4

Charts play a critical role in data analysis and visualization, yet real-world applications often present charts with challenging or noisy features. However, "outlier charts" pose…

cs.CV2025

Exploring Video-Based Driver Activity Recognition under Noisy Labels

Linjuan Fan, Di Wen, Kunyu Peng +8

As an open research topic in the field of deep learning, learning with noisy labels has attracted much attention and grown rapidly over the past ten years. Learning with label nois…

cs.CV2025

Scene-agnostic Pose Regression for Visual Localization

Junwei Zheng, Ruiping Liu, Yufan Chen +4

Absolute Pose Regression (APR) predicts 6D camera poses but lacks the adaptability to unknown environments without retraining, while Relative Pose Regression (RPR) generalizes bett…

cs.CV2025

RefChartQA: Grounding Visual Answer on Chart Images through Instruction Tuning

Alexander Vogel, Omar Moured, Yufan Chen +2

Recently, Vision Language Models (VLMs) have increasingly emphasized document visual grounding to achieve better human-computer interaction, accessibility, and detailed understandi…

cs.CV2025

SFDLA: Source-Free Document Layout Analysis

Sebastian Tewes, Yufan Chen, Omar Moured +2

Document Layout Analysis (DLA) is a fundamental task in document understanding. However, existing DLA and adaptation methods often require access to large-scale source data and tar…

cs.CV2025

Graph-based Document Structure Analysis

Yufan Chen, Ruiping Liu, Junwei Zheng +4

When reading a document, glancing at the spatial layout of a document is an initial step to understand it roughly. Traditional document layout analysis (DLA) methods, however, offe…