1 citations · 1 across the 6 of their papers we have counts for
7 papers
When Pairwise Preferences Cycle: A Reliability-Anchored Preference Walk for Video GRPO
Xinrui Lin, Fan Li, Shumin Wang +2
Pairwise preference feedback has become a widely adopted supervision signal for reinforcement learning in video generation models, as pairwise comparisons provide a more reliable a…
ShotCrop: Cropping Human-Centric Images into Cinematic Triple-Shot Compositions
Dehong Kong, Lina Lei, Lingtao Zheng +10
Prior work on aesthetic composition typically produces a single aesthetically pleasing crop, overlooking the narrative value of composing multiple shots from one scene. In practice…
YOSE: You Only Select Essential Tokens for Efficient DiT-based Video Object Removal
Chenyang Wu, Lina Lei, Fan Li +6
Recent advances in Diffusion Transformer (DiT)-based video generation technologies have shown impressive results for video object removal. However, these methods still suffer from…
UI2V-Bench: An Understanding-based Image-to-video Generation Benchmark
Ailing Zhang, Lina Lei, Dehong Kong +7
Generative diffusion models are developing rapidly and attracting increasing attention due to their wide range of applications. Image-to-Video (I2V) generation has become a major f…
Universal Camouflage Attack on Vision-Language Models for Autonomous Driving
Dehong Kong, Sifan Yu, Siyuan Liang +4
Visual language modeling for automated driving is emerging as a promising research direction with substantial improvements in multimodal reasoning capabilities. Despite its advance…
Dual Prompting Image Restoration with Diffusion Transformers
Dehong Kong, Fan Li, Zhixin Wang +4
Recent state-of-the-art image restoration methods mostly adopt latent diffusion models with U-Net backbones, yet still facing challenges in achieving high-quality restoration due t…
Environmental Matching Attack Against Unmanned Aerial Vehicles Object Detection
Dehong Kong, Siyuan Liang, Wenqi Ren
Object detection techniques for Unmanned Aerial Vehicles (UAVs) rely on Deep Neural Networks (DNNs), which are vulnerable to adversarial attacks. Nonetheless, adversarial patches g…