9 citations · 26 across the 12 of their papers we have counts for
12 papers · 1 filter
GenCompositor: Generative Video Compositing with Diffusion Transformer
Shuzhou Yang, Xiaoyu Li, Xiaodong Cun +4
Video compositing combines live-action footage to create video production, serving as a crucial technique in video creation and film production. Traditional pipelines require inten…
4DVD: Cascaded Dense-view Video Diffusion Model for High-quality 4D Content Generation
Shuzhou Yang, Xiaodong Cun, Xiaoyu Li +2
Given the high complexity of directly generating high-dimensional data such as 4D, we present 4DVD, a cascaded video diffusion model that generates 4D content in a decoupled manner…
SecureGS: Boosting the Security and Fidelity of 3D Gaussian Splatting Steganography
Xuanyu Zhang, Jiarui Meng, Zhipei Xu +4
3D Gaussian Splatting (3DGS) has emerged as a premier method for 3D representation due to its real-time rendering and high-quality outputs, underscoring the critical need to protec…
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…
Mirror-3DGS: Incorporating Mirror Reflections into 3D Gaussian Splatting
Jiarui Meng, Haijie Li, Yanmin Wu +4
3D Gaussian Splatting (3DGS) has significantly advanced 3D scene reconstruction and novel view synthesis. However, like Neural Radiance Fields (NeRF), 3DGS struggles with accuratel…
Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model
Dian Zheng, Xiao-Ming Wu, Shuzhou Yang +3
Universal image restoration is a practical and potential computer vision task for real-world applications. The main challenge of this task is handling the different degradation dis…
ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation
Zihan Li, Yuan Zheng, Dandan Shan +6
Most recent scribble-supervised segmentation methods commonly adopt a CNN framework with an encoder-decoder architecture. Despite its multiple benefits, this framework generally ca…
Neural Video Fields Editing
Shuzhou Yang, Chong Mou, Jiwen Yu +3
Diffusion models have revolutionized text-driven video editing. However, applying these methods to real-world editing encounters two significant challenges: (1) the rapid increase…
DiffLLE: Diffusion-guided Domain Calibration for Unsupervised Low-light Image Enhancement
Shuzhou Yang, Xuanyu Zhang, Yinhuai Wang +3
Existing unsupervised low-light image enhancement methods lack enough effectiveness and generalization in practical applications. We suppose this is because of the absence of expli…
Contrastive Learning Based Recursive Dynamic Multi-Scale Network for Image Deraining
Zhiying Jiang, Risheng Liu, Shuzhou Yang +2
Rain streaks significantly decrease the visibility of captured images and are also a stumbling block that restricts the performance of subsequent computer vision applications. The…
Implicit Neural Representation for Cooperative Low-light Image Enhancement
Shuzhou Yang, Moxuan Ding, Yanmin Wu +2
The following three factors restrict the application of existing low-light image enhancement methods: unpredictable brightness degradation and noise, inherent gap between metric-fa…
NeRFocus: Neural Radiance Field for 3D Synthetic Defocus
Yinhuai Wang, Shuzhou Yang, Yujie Hu +1
Neural radiance fields (NeRF) bring a new wave for 3D interactive experiences. However, as an important part of the immersive experiences, the defocus effects have not been fully e…