5 papers
Multimodal 3D LUT Generation via StatLUT with Statistical Features for Photorealistic Style Transfer
Yifan Wang, Zhixiang Hao, Yu Wang +1
Photorealistic Style Transfer (PST) aims to transfer the color and tonal style of a reference to a content image while strictly preserving its structural integrity. However, existi…
SALAD: Achieve High-Sparsity Attention via Efficient Linear Attention Tuning for Video Diffusion Transformer
Tongcheng Fang, Hanling Zhang, Ruiqi Xie +8
Diffusion Transformers have demonstrated remarkable performance in video generation. However, their long input sequences incur substantial latency due to the quadratic complexity o…
db-SP: Accelerating Sparse Attention for Visual Generative Models with Dual-Balanced Sequence Parallelism
Siqi Chen, Ke Hong, Tianchen Zhao +4
Scaling Diffusion Transformer (DiT) inference via sequence parallelism is critical for reducing latency in visual generation, but is severely hampered by workload imbalance when ap…
LRQ-DiT: Log-Rotation Post-Training Quantization of Diffusion Transformers for Image and Video Generation
Lianwei Yang, Haokun Lin, Tianchen Zhao +6
Diffusion Transformers (DiTs) have achieved impressive performance in text-to-image and text-to-video generation. However, their high computational cost and large parameter sizes p…
Hybrid Fourier Score Distillation for Efficient One Image to 3D Object Generation
Shuzhou Yang, Yu Wang, Haijie Li +4
Single image-to-3D generation is pivotal for crafting controllable 3D assets. Given its under-constrained nature, we attempt to leverage 3D geometric priors from a novel view diffu…