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20242026
most citedMobileMamba: Lightweight Multi-Receptive Visual Mamba Network

6 citations · 16 across the 55 of their papers we have counts for

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28 papers · 1 filter

cs.CV2025

Soul: Breathe Life into Digital Human for High-fidelity Long-term Multimodal Animation

Jiangning Zhang, Junwei Zhu, Zhenye Gan +14

We propose a multimodal-driven framework for high-fidelity long-term digital human animation termed , which generates semantically coherent videos from a single-fram…

cs.CV2025

Transform Trained Transformer for Accelerating Native 4K Video Generation

Jiangning Zhang, Junwei Zhu, Teng Hu +9

Native 4K (21763840) video generation remains a critical challenge due to the quadratic computational explosion of full-attention as spatiotemporal resolution increases, ma…

cs.AI2025

Med-CMR: A Fine-Grained Benchmark Integrating Visual Evidence and Clinical Logic for Medical Complex Multimodal Reasoning

Haozhen Gong, Xiaozhong Ji, Yuansen Liu +9

MLLMs MLLMs are beginning to appear in clinical workflows, but their ability to perform complex medical reasoning remains unclear. We present Med-CMR, a fine-grained Medical Comple…

cs.CV2025

Boosting Reasoning in Large Multimodal Models via Activation Replay

Yun Xing, Xiaobin Hu, Qingdong He +4

Recently, Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as an effective approach to incentivizing reasoning capability in Large Multimodal Models (LMMs), while…

cs.CV2025

DiP: Taming Diffusion Models in Pixel Space

Zhennan Chen, Junwei Zhu, Xu Chen +6

Diffusion models face a fundamental trade-off between generation quality and computational efficiency. Latent Diffusion Models (LDMs) offer an efficient solution but suffer from po…

cs.CV2025

FeRA: Frequency-Energy Constrained Routing for Effective Diffusion Adaptation Fine-Tuning

Bo Yin, Xiaobin Hu, Xingyu Zhou +7

Diffusion models have achieved remarkable success in generative modeling, yet how to effectively adapt large pretrained models to new tasks remains challenging. We revisit the reco…

cs.CV2025

Towards One-step Causal Video Generation via Adversarial Self-Distillation

Yongqi Yang, Huayang Huang, Xu Peng +5

Recent hybrid video generation models combine autoregressive temporal dynamics with diffusion-based spatial denoising, but their sequential, iterative nature leads to error accumul…

cs.CV2025

OracleAgent: A Multimodal Reasoning Agent for Oracle Bone Script Research

Caoshuo Li, Zengmao Ding, Xiaobin Hu +13

As one of the earliest writing systems, Oracle Bone Script (OBS) preserves the cultural and intellectual heritage of ancient civilizations. However, current OBS research faces two…

cs.CV2025

TokenAR: Multiple Subject Generation via Autoregressive Token-level enhancement

Haiyue Sun, Qingdong He, Jinlong Peng +5

Autoregressive Model (AR) has shown remarkable success in conditional image generation. However, these approaches for multiple reference generation struggle with decoupling differe…

cs.CV2025

Human-MME: A Holistic Evaluation Benchmark for Human-Centric Multimodal Large Language Models

Yuansen Liu, Haiming Tang, Jinlong Peng +12

Multimodal Large Language Models (MLLMs) have demonstrated significant advances in visual understanding tasks. However, their capacity to comprehend human-centric scenes has rarely…

cs.CL2025

LLM-Oriented Token-Adaptive Knowledge Distillation

Xurong Xie, Zhucun Xue, Jiafu Wu +5

Knowledge distillation (KD) is a key technique for compressing large-scale language models (LLMs), yet prevailing logit-based methods typically employ static strategies that are mi…

cs.CV2025

IVEBench: Modern Benchmark Suite for Instruction-Guided Video Editing Assessment

Yinan Chen, Jiangning Zhang, Teng Hu +7

Instruction-guided video editing has emerged as a rapidly advancing research direction, offering new opportunities for intuitive content transformation while also posing significan…

cs.MA2025

Visual Multi-Agent System: Mitigating Hallucination Snowballing via Visual Flow

Xinlei Yu, Chengming Xu, Guibin Zhang +8

Multi-Agent System (MAS) powered by Visual Language Models (VLMs) enables challenging tasks but suffers from a novel failure term, multi-agent visual hallucination snowballing, whe…

cs.CV2025

StrandDesigner: Towards Practical Strand Generation with Sketch Guidance

Na Zhang, Moran Li, Chengming Xu +6

Realistic hair strand generation is crucial for applications like computer graphics and virtual reality. While diffusion models can generate hairstyles from text or images, these i…

cs.CV2025

Collaborative Face Experts Fusion in Video Generation: Boosting Identity Consistency Across Large Face Poses

Yuji Wang, Moran Li, Xiaobin Hu +7

Current video generation models struggle with identity preservation under large face poses, primarily facing two challenges: the difficulty in exploring an effective mechanism to i…

cs.CV2025

Visual Document Understanding and Reasoning: A Multi-Agent Collaboration Framework with Agent-Wise Adaptive Test-Time Scaling

Xinlei Yu, Chengming Xu, Zhangquan Chen +6

The dominant paradigm of monolithic scaling in Vision-Language Models (VLMs) is failing for understanding and reasoning in documents, yielding diminishing returns as it struggles w…

cs.CV2025

Semantic Frame Interpolation

Yijia Hong, Jiangning Zhang, Ran Yi +4

Generating intermediate video content of varying lengths based on given first and last frames, along with text prompt information, offers significant research and application poten…

cs.CV2025

HumanVideo-MME: Benchmarking MLLMs for Human-Centric Video Understanding

Yuxuan Cai, Jiangning Zhang, Zhenye Gan +9

Multimodal Large Language Models (MLLMs) have demonstrated significant advances in visual understanding tasks involving both images and videos. However, their capacity to comprehen…

cs.CV2025

Identity-Preserving Text-to-Video Generation Guided by Simple yet Effective Spatial-Temporal Decoupled Representations

Yuji Wang, Moran Li, Xiaobin Hu +7

Identity-preserving text-to-video (IPT2V) generation, which aims to create high-fidelity videos with consistent human identity, has become crucial for downstream applications. Howe…

cs.CV2025

Reasoning to Edit: Hypothetical Instruction-Based Image Editing with Visual Reasoning

Qingdong He, Xueqin Chen, Chaoyi Wang +7

Instruction-based image editing (IIE) has advanced rapidly with the success of diffusion models. However, existing efforts primarily focus on simple and explicit instructions to ex…

cs.CV2025

OracleFusion: Assisting the Decipherment of Oracle Bone Script with Structurally Constrained Semantic Typography

Caoshuo Li, Zengmao Ding, Xiaobin Hu +10

As one of the earliest ancient languages, Oracle Bone Script (OBS) encapsulates the cultural records and intellectual expressions of ancient civilizations. Despite the discovery of…

cs.CV2025

Align and Surpass Human Camouflaged Perception: Visual Refocus Reinforcement Fine-Tuning

Ruolin Shen, Xiaozhong Ji, Kai WU +5

Current multi-modal models exhibit a notable misalignment with the human visual system when identifying objects that are visually assimilated into the background. Our observations…

cs.CV2025

VTBench: Comprehensive Benchmark Suite Towards Real-World Virtual Try-on Models

Hu Xiaobin, Liang Yujie, Luo Donghao +5

While virtual try-on has achieved significant progress, evaluating these models towards real-world scenarios remains a challenge. A comprehensive benchmark is essential for three k…

cs.CV2025

DVHGNN: Multi-Scale Dilated Vision HGNN for Efficient Vision Recognition

Caoshuo Li, Tanzhe Li, Xiaobin Hu +2

Recently, Vision Graph Neural Network (ViG) has gained considerable attention in computer vision. Despite its groundbreaking innovation, Vision Graph Neural Network encounters key…