12 papers
UltraDiff: Transferring High-Fidelity Priors to Compressed Latent Spaces for High-Resolution Image Generation
Jingjing Ren, Haitian Zheng, Haoyu Chen +5
High-resolution synthesis with Latent Diffusion Models (LDMs) faces a fundamental trade-off between computational cost and generative fidelity. This trade off is largely governed b…
Adversarial Training for Pixel Diffusion
Xin Lin, Zhifei Zhang, Yuqian Zhou +4
Pixel diffusion models generate RGB images directly, avoiding the bottleneck of an autoencoder, yet their outputs still systematically underrepresent fine-scale natural-image stati…
DMA: Pixel-space Distribution Matching with Adversarial and Anchor Losses
Xin Lin, Zhifei Zhang, Yuqian Zhou +6
Distribution matching distillation (DMD) provides a general framework for few-step diffusion generation, but its modern text-to-image instantiations have been developed primarily a…
EditStream: A Unified Autoregressive Framework for Interactive Video Generation and Editing
Yuqian Zhou, Zhenghong Zhou, Zongze Wu +5
Interactive video generation and editing are becoming increasingly important for creative design. In this report, we introduce EditStream: a unified framework for interactive video…
PixelControl: Fine-Grained Condition Fidelity in Text-to-Image Diffusion
Xin Lin, Haodong Li, Zhifei Zhang +5
Controllable text-to-image diffusion models can often follow the global layout of spatial conditions, yet still violate fine-grained structures such as object boundaries, thin cont…
Tri-Prompting: Video Diffusion with Unified Control over Scene, Subject, and Motion
Zhenghong Zhou, Xiaohang Zhan, Zhiqin Chen +8
Recent video diffusion models achieve strong visual quality and temporal coherence, but still lack coordinated control over scene layout, customized subject identity, and camera/su…
SNCE: Geometry-Aware Supervision for Scalable Discrete Image Generation
Shufan Li, Jiuxiang Gu, Kangning Liu +3
Recent advancements in discrete image generation showed that scaling the VQ codebook size significantly improves reconstruction fidelity. However, training generative models with a…
PixPerfect: Seamless Latent Diffusion Local Editing with Discriminative Pixel-Space Refinement
Haitian Zheng, Yuan Yao, Yongsheng Yu +3
Latent Diffusion Models (LDMs) have markedly advanced the quality of image inpainting and local editing. However, the inherent latent compression often introduces pixel-level incon…
HBridge: H-Shape Bridging of Heterogeneous Experts for Unified Multimodal Understanding and Generation
Xiang Wang, Zhifei Zhang, He Zhang +11
Recent unified models integrate understanding experts (e.g., LLMs) with generative experts (e.g., diffusion models), achieving strong multimodal performance. However, recent advanc…
ZipIR: Latent Pyramid Diffusion Transformer for High-Resolution Image Restoration
Yongsheng Yu, Haitian Zheng, Zhifei Zhang +7
Recent progress in generative models has significantly improved image restoration capabilities, particularly through powerful diffusion models that offer remarkable recovery of sem…
TurboFill: Adapting Few-step Text-to-image Model for Fast Image Inpainting
Liangbin Xie, Daniil Pakhomov, Zhonghao Wang +8
This paper introduces TurboFill, a fast image inpainting model that enhances a few-step text-to-image diffusion model with an inpainting adapter for high-quality and efficient inpa…
Baking Gaussian Splatting into Diffusion Denoiser for Fast and Scalable Single-stage Image-to-3D Generation and Reconstruction
Yuanhao Cai, He Zhang, Kai Zhang +12
Existing feedforward image-to-3D methods mainly rely on 2D multi-view diffusion models that cannot guarantee 3D consistency. These methods easily collapse when changing the prompt…