5 papers · 1 filter
DiffSparse: Accelerating Diffusion Transformers with Learned Token Sparsity
Haowei Zhu, Ji Liu, Ziqiong Liu +4
Diffusion models demonstrate outstanding performance in image generation, but their multi-step inference mechanism requires immense computational cost. Previous works accelerate in…
Mango-GS: Enhancing Spatio-Temporal Consistency in Dynamic Scenes Reconstruction using Multi-Frame Node-Guided 4D Gaussian Splatting
Tingxuan Huang, Haowei Zhu, Jun-hai Yong +2
Reconstructing dynamic 3D scenes with photorealistic detail and strong temporal coherence remains a significant challenge. Existing Gaussian splatting approaches for dynamic scene…
ReCon: Region-Controllable Data Augmentation with Rectification and Alignment for Object Detection
Haowei Zhu, Tianxiang Pan, Rui Qin +2
The scale and quality of datasets are crucial for training robust perception models. However, obtaining large-scale annotated data is both costly and time-consuming. Generative mod…
Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning
Haowei Zhu, Fangyuan Zhang, Rui Qin +3
As the scale of vision models continues to grow, Visual Prompt Tuning (VPT) has emerged as a parameter-efficient transfer learning technique, noted for its superior performance com…
DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization
Haowei Zhu, Dehua Tang, Ji Liu +12
Diffusion models have achieved remarkable progress in the field of image generation due to their outstanding capabilities. However, these models require substantial computing resou…