27 citations · 80 across the 96 of their papers we have counts for
19 papers · 2 filters
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…
OmniTrack++: Omnidirectional Multi-Object Tracking by Learning Large-FoV Trajectory Feedback
Kai Luo, Hao Shi, Kunyu Peng +4
To address panoramic distortion, large search space, and identity ambiguity under a 360° FoV, OmniTrack++ adopts a feedback-driven framework that progressively refines perception w…
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…
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…
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…
Exploring Single Domain Generalization of LiDAR-based Semantic Segmentation under Imperfect Labels
Weitong Kong, Zichao Zeng, Di Wen +5
Accurate perception is critical for vehicle safety, with LiDAR as a key enabler in autonomous driving. To ensure robust performance across environments, sensor types, and weather c…
Segment-to-Act: Label-Noise-Robust Action-Prompted Video Segmentation Towards Embodied Intelligence
Wenxin Li, Kunyu Peng, Di Wen +4
Embodied intelligence relies on accurately segmenting objects actively involved in interactions. Action-based video object segmentation addresses this by linking segmentation with…
T-MASK: Temporal Masking for Probing Foundation Models across Camera Views in Driver Monitoring
Thinesh Thiyakesan Ponbagavathi, Kunyu Peng, Alina Roitberg
Changes of camera perspective are a common obstacle in driver monitoring. While deep learning and pretrained foundation models show strong potential for improved generalization via…
Unlocking Constraints: Source-Free Occlusion-Aware Seamless Segmentation
Yihong Cao, Jiaming Zhang, Xu Zheng +5
Panoramic image processing is essential for omni-context perception, yet faces constraints like distortions, perspective occlusions, and limited annotations. Previous unsupervised…
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…
Hallucinating 360°: Panoramic Street-View Generation via Local Scenes Diffusion and Probabilistic Prompting
Fei Teng, Kai Luo, Sheng Wu +6
Panoramic perception holds significant potential for autonomous driving, enabling vehicles to acquire a comprehensive 360° surround view in a single shot. However, autonomous drivi…
Out-of-Distribution Semantic Occupancy Prediction
Yuheng Zhang, Mengfei Duan, Kunyu Peng +6
3D semantic occupancy prediction is crucial for autonomous driving, providing a dense, semantically rich environmental representation. However, existing methods focus on in-distrib…
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.…
Diffusion-based Cumulative Adversarial Purification for Vision Language Models
Jia Fu, Yongtao Wu, Yihang Chen +5
Vision Language Models (VLMs) have shown remarkable capabilities in multimodal understanding, yet their susceptibility to adversarial perturbations poses a significant threat to th…
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…
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…
LFX: Towards Unified Light Field Dense Semantic Segmentation and Salient Object Detection
Fei Teng, Lingxin Huang, Buyin Deng +8
Light field cameras capture multi-view observations within a single exposure. However, existing studies are typically tailored to specific LF representations, leaving the field wit…
MindAligner: Explicit Brain Functional Alignment for Cross-Subject Visual Decoding from Limited fMRI Data
Yuqin Dai, Zhouheng Yao, Chunfeng Song +7
Brain decoding aims to reconstruct visual perception of human subject from fMRI signals, which is crucial for understanding brain's perception mechanisms. Existing methods are conf…
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…