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20242026
most citedTowards Global Optimal Visual In-Context Learning Prompt Selection

1 citations · 4 across the 28 of their papers we have counts for

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11 papers · 1 filter

cs.CV2025

LongVie 2: Multimodal Controllable Ultra-Long Video World Model

Jianxiong Gao, Zhaoxi Chen, Xian Liu +7

Building video world models upon pretrained video generation systems represents an important yet challenging step toward general spatiotemporal intelligence. A world model should p…

cs.CV2025

VisMem: Latent Vision Memory Unlocks Potential of Vision-Language Models

Xinlei Yu, Chengming Xu, Guibin Zhang +7

Despite the remarkable success of Vision-Language Models (VLMs), their performance on a range of complex visual tasks is often hindered by a "visual processing bottleneck": a prope…

cs.CV2025

Towards Reliable and Holistic Visual In-Context Learning Prompt Selection

Wenxiao Wu, Jing-Hao Xue, Chengming Xu +5

Visual In-Context Learning (VICL) has emerged as a prominent approach for adapting visual foundation models to novel tasks, by effectively exploiting contextual information embedde…

cs.CV2025

SwiftVideo: A Unified Framework for Few-Step Video Generation through Trajectory-Distribution Alignment

Yanxiao Sun, Jiafu Wu, Yun Cao +6

Diffusion-based or flow-based models have achieved significant progress in video synthesis but require multiple iterative sampling steps, which incurs substantial computational ove…

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

Disentangle Identity, Cooperate Emotion: Correlation-Aware Emotional Talking Portrait Generation

Weipeng Tan, Chuming Lin, Chengming Xu +6

Recent advances in Talking Head Generation (THG) have achieved impressive lip synchronization and visual quality through diffusion models; yet existing methods struggle to generate…

cs.CV2025

When Preferences Diverge: Aligning Diffusion Models with Minority-Aware Adaptive DPO

Lingfan Zhang, Chen Liu, Chengming Xu +5

In recent years, the field of image generation has witnessed significant advancements, particularly in fine-tuning methods that align models with universal human preferences. This…

cs.CV2025

CrossVTON: Mimicking the Logic Reasoning on Cross-category Virtual Try-on guided by Tri-zone Priors

Donghao Luo, Yujie Liang, Xu Peng +6

Despite remarkable progress in image-based virtual try-on systems, generating realistic and robust fitting images for cross-category virtual try-on remains a challenging task. The…

cs.CV2025

SVFR: A Unified Framework for Generalized Video Face Restoration

Zhiyao Wang, Xu Chen, Chengming Xu +7

Face Restoration (FR) is a crucial area within image and video processing, focusing on reconstructing high-quality portraits from degraded inputs. Despite advancements in image FR,…