activity
20232026
most citedHybridOcc: NeRF Enhanced Transformer-based Multi-Camera 3D Occupancy Prediction

12 citations · 54 across the 33 of their papers we have counts for

collaborators

34 papers

cs.RO2026

UniWAM Technical Report: Unified Mobile Manipulation via Mixed-Stream World-Action Modeling and Manipulation Anchor Pose Supervision

Wei Xue, Keliang Liu, Mingzhang Cui +14

Mobile manipulation requires precise navigation to a manipulation-ready pose followed by reliable object interaction. These two stages differ in action spaces and visual requiremen…

cs.RO2026

ProFocus: Proactive Perception and Focused Reasoning in Vision-and-Language Navigation

Wei Xue, Mingcheng Li, Xuecheng Wu +3

Vision-and-Language Navigation (VLN) requires agents to accurately perceive complex visual environments and reason over navigation instructions and histories. However, existing met…

cs.CV2025

FysicsWorld: A Unified Full-Modality Benchmark for Any-to-Any Understanding, Generation, and Reasoning

Yue Jiang, Dingkang Yang, Minghao Han +6

Despite rapid progress in multimodal large language models (MLLMs) and emerging omni-modal architectures, current benchmarks remain limited in scope and integration, suffering from…

cs.CV2025

SatireDecoder: Visual Cascaded Decoupling for Enhancing Satirical Image Comprehension

Yue Jiang, Haiwei Xue, Minghao Han +5

Satire, a form of artistic expression combining humor with implicit critique, holds significant social value by illuminating societal issues. Despite its cultural and societal sign…

cs.CV2025

Resolving Evidence Sparsity: Agentic Context Engineering for Long-Document Understanding

Keliang Liu, Zizhi Chen, Mingcheng Li +3

Document understanding is a long standing practical task. Vision Language Models (VLMs) have gradually become a primary approach in this domain, demonstrating effective performance…

cs.CV2025★ 1 cited

Improving Multimodal Sentiment Analysis via Modality Optimization and Dynamic Primary Modality Selection

Dingkang Yang, Mingcheng Li, Xuecheng Wu +5

Multimodal Sentiment Analysis (MSA) aims to predict sentiment from language, acoustic, and visual data in videos. However, imbalanced unimodal performance often leads to suboptimal…

cs.LG2025

FSRF: Factorization-guided Semantic Recovery for Incomplete Multimodal Sentiment Analysis

Ziyang Liu, Pengjunfei Chu, Shuming Dong +3

In recent years, Multimodal Sentiment Analysis (MSA) has become a research hotspot that aims to utilize multimodal data for human sentiment understanding. Previous MSA studies have…

cs.LG2025

COPO: Consistency-Aware Policy Optimization

Jinghang Han, Jiawei Chen, Hang Shao +7

Reinforcement learning has significantly enhanced the reasoning capabilities of Large Language Models (LLMs) in complex problem-solving tasks. Recently, the introduction of DeepSee…

cs.CV2025

PersonaAnimator: Personalized Motion Transfer from Unconstrained Videos

Ziyun Qian, Runyu Xiao, Shuyuan Tu +7

Recent advances in motion generation show remarkable progress. However, several limitations remain: (1) Existing pose-guided character motion transfer methods merely replicate moti…

cs.AI2025

Learning, Reasoning, Refinement: A Framework for Kahneman's Dual-System Intelligence in GUI Agents

Jinjie Wei, Jiyao Liu, Lihao Liu +8

Graphical User Interface (GUI) agents have made significant progress in automating digital tasks through the utilization of computer vision and language models. Nevertheless, exist…

cs.CV2025

MCCD: Multi-Agent Collaboration-based Compositional Diffusion for Complex Text-to-Image Generation

Mingcheng Li, Xiaolu Hou, Ziyang Liu +7

Diffusion models have shown excellent performance in text-to-image generation. Nevertheless, existing methods often suffer from performance bottlenecks when handling complex prompt…

cs.CV2025

BloomScene: Lightweight Structured 3D Gaussian Splatting for Crossmodal Scene Generation

Xiaolu Hou, Mingcheng Li, Dingkang Yang +7

With the widespread use of virtual reality applications, 3D scene generation has become a new challenging research frontier. 3D scenes have highly complex structures and need to en…

cs.CL2024

Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning

Mingcheng Li, Dingkang Yang, Yang Liu +11

Multimodal Sentiment Analysis (MSA) is an important research area that aims to understand and recognize human sentiment through multiple modalities. The complementary information p…

cs.CL2024★ 2 cited

MedAide: Information Fusion and Anatomy of Medical Intents via LLM-based Agent Collaboration

Dingkang Yang, Jinjie Wei, Mingcheng Li +8

In healthcare intelligence, the ability to fuse heterogeneous, multi-intent information from diverse clinical sources is fundamental to building reliable decision-making systems. L…

cs.CV2024

MaskBEV: Towards A Unified Framework for BEV Detection and Map Segmentation

Xiao Zhao, Xukun Zhang, Dingkang Yang +4

Accurate and robust multimodal multi-task perception is crucial for modern autonomous driving systems. However, current multimodal perception research follows independent paradigms…

cs.CV2024★ 12 cited

HybridOcc: NeRF Enhanced Transformer-based Multi-Camera 3D Occupancy Prediction

Xiao Zhao, Bo Chen, Mingyang Sun +7

Vision-based 3D semantic scene completion (SSC) describes autonomous driving scenes through 3D volume representations. However, the occlusion of invisible voxels by scene surfaces…

cs.CV2024

Faster Diffusion Action Segmentation

Shuaibing Wang, Shunli Wang, Mingcheng Li +4

Temporal Action Segmentation (TAS) is an essential task in video analysis, aiming to segment and classify continuous frames into distinct action segments. However, the ambiguous bo…

cs.CL2024

Improving Factuality in Large Language Models via Decoding-Time Hallucinatory and Truthful Comparators

Dingkang Yang, Dongling Xiao, Jinjie Wei +4

Despite their remarkable capabilities, Large Language Models (LLMs) are prone to generate responses that contradict verifiable facts, i.e., unfaithful hallucination content. Existi…

cs.CV2024

Asynchronous Multimodal Video Sequence Fusion via Learning Modality-Exclusive and -Agnostic Representations

Dingkang Yang, Mingcheng Li, Linhao Qu +4

Understanding human intentions (e.g., emotions) from videos has received considerable attention recently. Video streams generally constitute a blend of temporal data stemming from…

cs.CV2024★ 4 cited

CoMT: Chain-of-Medical-Thought Reduces Hallucination in Medical Report Generation

Yue Jiang, Jiawei Chen, Dingkang Yang +5

Automatic medical report generation (MRG), which possesses significant research value as it can aid radiologists in clinical diagnosis and report composition, has garnered increasi…

cs.CV2024★ 7 cited

Detecting and Evaluating Medical Hallucinations in Large Vision Language Models

Jiawei Chen, Dingkang Yang, Tong Wu +7

Large Vision Language Models (LVLMs) are increasingly integral to healthcare applications, including medical visual question answering and imaging report generation. While these mo…

cs.CL2024★ 5 cited

PediatricsGPT: Large Language Models as Chinese Medical Assistants for Pediatric Applications

Dingkang Yang, Jinjie Wei, Dongling Xiao +11

Developing intelligent pediatric consultation systems offers promising prospects for improving diagnostic efficiency, especially in China, where healthcare resources are scarce. De…

cs.CV2024

SMCD: High Realism Motion Style Transfer via Mamba-based Diffusion

Ziyun Qian, Zeyu Xiao, Xingliang Jin +6

Motion style transfer is a significant research direction in the field of computer vision, enabling virtual digital humans to rapidly switch between different styles of the same mo…

cs.CV2024★ 1 cited

Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Models

Jiawei Chen, Dingkang Yang, Yue Jiang +4

In the realm of Medical Visual Language Models (Med-VLMs), the quest for universal efficient fine-tuning mechanisms remains paramount, especially given researchers in interdiscipli…