activity
20232026
most citedHolistic Autonomous Driving Understanding by Bird's-Eye-View Injected Multi-Modal Large Models

5 citations · 8 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2026

Beyond Frame Selection: Generative Latent Evidence Aggregation for Long-Video Understanding

Bowen Liu, Shuning Wang, Xinpeng Ding +3

Long-video understanding commonly compresses videos into a small set of frames or visual tokens for answer generation. Existing compact pipelines focus on retaining relevant visual…

cs.CV2026

MedHorizon: Towards Long-context Medical Video Understanding in the Wild

Bodong Du, Bowen Liu, Yang Yu +8

Medical multimodal large language models (MLLMs) have advanced image understanding and short-video analysis, but real clinical review often requires full-procedure video understand…

cs.CV2025

PaMi-VDPO: Mitigating Video Hallucinations by Prompt-Aware Multi-Instance Video Preference Learning

Xinpeng Ding, Kui Zhang, Jianhua Han +3

Direct Preference Optimization (DPO) helps reduce hallucinations in Video Multimodal Large Language Models (VLLMs), but its reliance on offline preference data limits adaptability…

eess.IV2024

Tri-Plane Mamba: Efficiently Adapting Segment Anything Model for 3D Medical Images

Hualiang Wang, Yiqun Lin, Xinpeng Ding +1

General networks for 3D medical image segmentation have recently undergone extensive exploration. Behind the exceptional performance of these networks lies a significant demand for…

eess.IV2024★ 1 cited

C^2RV: Cross-Regional and Cross-View Learning for Sparse-View CBCT Reconstruction

Yiqun Lin, Jiewen Yang, Hualiang Wang +3

Cone beam computed tomography (CBCT) is an important imaging technology widely used in medical scenarios, such as diagnosis and preoperative planning. Using fewer projection views…

cs.CV2024★ 5 cited

Holistic Autonomous Driving Understanding by Bird's-Eye-View Injected Multi-Modal Large Models

Xinpeng Ding, Jinahua Han, Hang Xu +3

The rise of multimodal large language models (MLLMs) has spurred interest in language-based driving tasks. However, existing research typically focuses on limited tasks and often o…

cs.CV2023★ 1 cited

GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation

Jiewen Yang, Xinpeng Ding, Ziyang Zheng +2

Echocardiogram video segmentation plays an important role in cardiac disease diagnosis. This paper studies the unsupervised domain adaption (UDA) for echocardiogram video segmentat…

cs.CV2023★ 1 cited

GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation

Ziyang Zheng, Jiewen Yang, Xinpeng Ding +2

Cardiac structure segmentation from echocardiogram videos plays a crucial role in diagnosing heart disease. The combination of multi-view echocardiogram data is essential to enhanc…

cs.CV2023

Context-Aware Pseudo-Label Refinement for Source-Free Domain Adaptive Fundus Image Segmentation

Zheang Huai, Xinpeng Ding, Yi Li +1

In the domain adaptation problem, source data may be unavailable to the target client side due to privacy or intellectual property issues. Source-free unsupervised domain adaptatio…