1 citations · 1 across the 24 of their papers we have counts for
26 papers
Socialized UAV Cross-Task Learning: Towards Cross-Granularity Collaboration through Hierarchical Interaction
Xinjie Yao, Ruipu Zhao, Yunqi Zhu +6
Joint learning across heterogeneous tasks is often treated as task coupling through feature sharing, distillation, or auxiliary supervision. However, in cross-task learning, mismat…
RIDGE: Re-Noising with Internal Dynamic Guidance for Image Editing
Ruiliang Gong, Zhen Wang, Yanghao Wang +1
Inversion-free flow-based image editing avoids latent inversion, but still requires a target-side state at every editing step. The widely used equal-displacement construction keeps…
h-Flow: Flexible Flow-based Image Editing via Doob's h-Transform
Zehui Guo, Zhen Wang, Junwei Shu +3
Editing images with pre-trained text-to-image flow models typically requires carefully balancing target alignment with the desired prompt and source consistency with the original i…
LISA: Likelihood Score Alignment for Visual-condition Controllable Generation
Yanghao Wang, Hongxu Chen, Jiazhen Liu +4
The prevalent dual-branch paradigm, i.e., training a side network to encode visual conditions and fusing its intermediate-layer features to a frozen pretrained main network, has sh…
Rethinking Air-Ground Collaboration: A Progressive Cross-Task Benchmark and Socialized Learning Framework
Zhoupeng Guo, Yunqi Zhu, Zhihe Fan +6
Air-ground collaborative perception is crucial for robust visual understanding in real-world dynamic environments. However, existing studies typically formulate collaboration as si…
RealCam: Real-Time Novel-View Video Generation with Interactive Camera Control
Youcan Xu, Jiaxin Shi, Zhen Wang +5
Camera-controlled video-to-video (V2V) generation enables dynamic viewpoint synthesis from monocular footage, holding immense potential for interactive filmmaking and live broadcas…
Direct Product Flow Matching: Decoupling Radial and Angular Dynamics for Few-Shot Adaptation
Hongxu Chen, Yanghao Wang, Bowei Zhu +6
Recent flow matching (FM) methods improve the few-shot adaptation of vision-language models, by modeling cross-modal alignment as a continuous multi-step flow. In this paper, we ar…
SteerFlow: Steering Rectified Flows for Faithful Inversion-Based Image Editing
Thinh Dao, Zhen Wang, Kien T. Pham +1
Recent advances in flow-based generative models have enabled training-free, text-guided image editing by inverting an image into its latent noise and regenerating it under a new ta…
FlowMotion: Training-Free Flow Guidance for Video Motion Transfer
Zhen Wang, Youcan Xu, Jun Xiao +1
Video motion transfer aims to generate a target video that inherits motion patterns from a source video while rendering new scenes. Existing training-free approaches focus on const…
Uncertainty-Aware 4D Gaussian Splatting for Monocular Occluded Human Rendering
Weiquan Wang, Feifei Shao, Lin Li +4
High-fidelity rendering of dynamic humans from monocular videos typically degrades catastrophically under occlusions. Existing solutions incorporate external priors-either hallucin…
AnyMS: Bottom-up Attention Decoupling for Layout-guided and Training-free Multi-subject Customization
Binhe Yu, Zhen Wang, Kexin Li +6
Multi-subject customization aims to synthesize multiple user-specified subjects into a coherent image. To address issues such as subjects missing or conflicts, recent works incorpo…
Bi-Anchor Interpolation Solver for Accelerating Generative Modeling
Hongxu Chen, Hongxiang Li, Zhen Wang +1
Flow Matching (FM) models have emerged as a leading paradigm for high-fidelity synthesis. However, their reliance on iterative Ordinary Differential Equation (ODE) solving creates…
FlowDC: Flow-Based Decoupling-Decay for Complex Image Editing
Yilei Jiang, Zhen Wang, Yanghao Wang +4
With the surge of pre-trained text-to-image flow matching models, text-based image editing performance has gained remarkable improvement, especially for \underline{simple editing}…
CoMo: Compositional Motion Customization for Text-to-Video Generation
Youcan Xu, Zhen Wang, Jiaxin Shi +6
While recent text-to-video models excel at generating diverse scenes, they struggle with precise motion control, particularly for complex, multi-subject motions. Although methods f…
Target-aware Image Editing via Cycle-consistent Constraints
Yanghao Wang, Zhen Wang, Long Chen
Recent pre-trained text-to-image flow models have enabled remarkable progress in text-based image editing. Mainstream approaches adopt a corruption-then-restoration paradigm, where…
FastFit: Accelerating Multi-Reference Virtual Try-On via Cacheable Diffusion Models
Zheng Chong, Yanwei Lei, Shiyue Zhang +7
Despite its great potential, virtual try-on technology is hindered from real-world application by two major challenges: the inability of current methods to support multi-reference…
Zero-Residual Concept Erasure via Progressive Alignment in Text-to-Image Model
Hongxu Chen, Zhen Wang, Taoran Mei +4
Concept Erasure, which aims to prevent pretrained text-to-image models from generating content associated with semantic-harmful concepts (i.e., target concepts), is getting increas…
Diffusion Restoration Adapter for Real-World Image Restoration
Hanbang Liang, Zhen Wang, Weihui Deng
Diffusion models have demonstrated their powerful image generation capabilities, effectively fitting highly complex image distributions. These models can serve as strong priors for…
PQD: Post-training Quantization for Efficient Diffusion Models
Jiaojiao Ye, Zhen Wang, Linnan Jiang
Diffusionmodels(DMs)havedemonstratedremarkableachievements in synthesizing images of high fidelity and diversity. However, the extensive computational requirements and slow generat…
IterIS: Iterative Inference-Solving Alignment for LoRA Merging
Hongxu Chen, Runshi Li, Bowei Zhu +2
Low-rank adaptations (LoRA) are widely used to fine-tune large models across various domains for specific downstream tasks. While task-specific LoRAs are often available, concerns…
CLIPDrag: Combining Text-based and Drag-based Instructions for Image Editing
Ziqi Jiang, Zhen Wang, Long Chen
Precise and flexible image editing remains a fundamental challenge in computer vision. Based on the modified areas, most editing methods can be divided into two main types: global…
Event-Customized Image Generation
Zhen Wang, Yilei Jiang, Dong Zheng +2
Customized Image Generation, generating customized images with user-specified concepts, has raised significant attention due to its creativity and novelty. With impressive progress…
FreeTuner: Any Subject in Any Style with Training-free Diffusion
Youcan Xu, Zhen Wang, Jun Xiao +2
With the advance of diffusion models, various personalized image generation methods have been proposed. However, almost all existing work only focuses on either subject-driven or s…
Improving Data Augmentation for Robust Visual Question Answering with Effective Curriculum Learning
Yuhang Zheng, Zhen Wang, Long Chen
Being widely used in learning unbiased visual question answering (VQA) models, Data Augmentation (DA) helps mitigate language biases by generating extra training samples beyond the…