6 papers · 1 filter
Aligning Human Sense: Calibrated Distributional Reward Learning for Video Generation
Nai-Xin Zhai, Weihua Cheng, Dexu Yu +9
Video generation is central to AI-powered content creation. Aligning generated videos with human preferences is a key criterion for evaluating generation quality. Despite significa…
FocusDiT: Masking Queries in Diffusion Transformers for Fine-grained Image Generation
Xueji Fang, Liyuan Ma, Jianhao Zeng +3
Diffusion transformer (DiT) has been widely adopted in the generative diffusion field, advancing the denoising of query tokens through attention and Feed-Forward (\text{FFN}) layer…
Equilibrated Diffusion: Frequency-aware Textual Embedding for Equilibrated Image Customization
Liyuan Ma, Xueji Fang, Guo-Jun Qi
Image customization learns target subjects from reference concept images and generates conditioned images per text prompts, mainly modifying styles or backgrounds. Prevailing metho…
When Images Speak Louder: Mitigating Language Bias-induced Hallucinations in VLMs through Cross-Modal Guidance
Jinjin Cao, Zhiyang Chen, Zijun Wang +3
Vision-Language Models (VLMs) have shown solid ability for multimodal understanding of both visual and language contexts. However, existing VLMs often face severe challenges of hal…
InfLVG: Reinforce Inference-Time Consistent Long Video Generation with GRPO
Xueji Fang, Liyuan Ma, Zhiyang Chen +2
Recent advances in text-to-video generation, particularly with autoregressive models, have enabled the synthesis of high-quality videos depicting individual scenes. However, extend…
Self-Guidance: Boosting Flow and Diffusion Generation on Their Own
Tiancheng Li, Weijian Luo, Zhiyang Chen +2
Proper guidance strategies are essential to achieve high-quality generation results without retraining diffusion and flow-based text-to-image models. Existing guidance either requi…