43 citations · 55 across the 17 of their papers we have counts for
17 papers
Struct-GStream: Towards Efficient Free-Viewpoint Video Streaming at Low-Bitrates with Structured 3D Gaussians
Han Jiao, Jiakai Sun, Lei Zhao +4
Constructing photorealistic Free-Viewpoint Videos (FVVs) of dynamic scenes from a set of posed 2D images has been an intriguing yet challenging task in computer vision. Methods bas…
A Cyclic Adaptation-Generalization Framework with Uncertainty-Guided Self-Paced Learning for Long-Term Brain-Machine Interfaces
Jiyu Wei, Di Hong, Zhanjie Zhang +3
Brain-Machine Interfaces (BMIs), which link the brain to external devices, hold great potential in rehabilitation, human performance augmentation, and human-centered robotics. Howe…
Self-Supervised Consistency Enhanced Disentangled Learning for Neural Decoding Generalization in Brain-Machine Interface
Jiyu Wei, Di Hong, Zhanjie Zhang +3
Brain-Machine Interfaces (BMIs) provide a direct communication pathway between the brain and external devices, enabling humans to control assistive and robotic technologies, with p…
RoadVGGT: Road-Structure-Aware Feed-Forward Road Surface Reconstruction
Han Jiao, Chen Liu, Jiakai Sun +6
Large-scale road surface reconstruction supports high-definition mapping, autonomous-driving perception, annotation, and simulation. Existing road-specialized optimization methods…
SMFormer: Empowering Self-supervised Stereo Matching via Foundation Models and Data Augmentation
Yun Wang, Zhengjie Yang, Jiahao Zheng +3
Recent self-supervised stereo matching methods have made significant progress. They typically rely on the photometric consistency assumption, which presumes corresponding points ac…
Fast and Robust Deformable 3D Gaussian Splatting
Han Jiao, Jiakai Sun, Lei Zhao +3
3D Gaussian Splatting has demonstrated remarkable real-time rendering capabilities and superior visual quality in novel view synthesis for static scenes. Building upon these advant…
SPAST: Arbitrary Style Transfer with Style Priors via Pre-trained Large-scale Model
Zhanjie Zhang, Quanwei Zhang, Junsheng Luan +3
Given an arbitrary content and style image, arbitrary style transfer aims to render a new stylized image which preserves the content image's structure and possesses the style image…
DyArtbank: Diverse Artistic Style Transfer via Pre-trained Stable Diffusion and Dynamic Style Prompt Artbank
Zhanjie Zhang, Quanwei Zhang, Guangyuan Li +4
Artistic style transfer aims to transfer the learned style onto an arbitrary content image. However, most existing style transfer methods can only render consistent artistic styliz…
Rethink Arbitrary Style Transfer with Transformer and Contrastive Learning
Zhanjie Zhang, Jiakai Sun, Guangyuan Li +7
Arbitrary style transfer holds widespread attention in research and boasts numerous practical applications. The existing methods, which either employ cross-attention to incorporate…
Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution
Guangyuan Li, Chen Rao, Juncheng Mo +3
Recently, diffusion models (DM) have been applied in magnetic resonance imaging (MRI) super-resolution (SR) reconstruction, exhibiting impressive performance, especially with regar…
Towards Highly Realistic Artistic Style Transfer via Stable Diffusion with Step-aware and Layer-aware Prompt
Zhanjie Zhang, Quanwei Zhang, Huaizhong Lin +9
Artistic style transfer aims to transfer the learned artistic style onto an arbitrary content image, generating artistic stylized images. Existing generative adversarial network-ba…
3DGStream: On-the-Fly Training of 3D Gaussians for Efficient Streaming of Photo-Realistic Free-Viewpoint Videos
Jiakai Sun, Han Jiao, Guangyuan Li +3
Constructing photo-realistic Free-Viewpoint Videos (FVVs) of dynamic scenes from multi-view videos remains a challenging endeavor. Despite the remarkable advancements achieved by c…
ArtBank: Artistic Style Transfer with Pre-trained Diffusion Model and Implicit Style Prompt Bank
Zhanjie Zhang, Quanwei Zhang, Guangyuan Li +7
Artistic style transfer aims to repaint the content image with the learned artistic style. Existing artistic style transfer methods can be divided into two categories: small model-…
VGOS: Voxel Grid Optimization for View Synthesis from Sparse Inputs
Jiakai Sun, Zhanjie Zhang, Jiafu Chen +5
Neural Radiance Fields (NeRF) has shown great success in novel view synthesis due to its state-of-the-art quality and flexibility. However, NeRF requires dense input views (tens to…
Joint Optimization of Triangle Mesh, Material, and Light from Neural Fields with Neural Radiance Cache
Jiakai Sun, Weijing Zhang, Zhanjie Zhang +4
Traditional inverse rendering techniques are based on textured meshes, which naturally adapts to modern graphics pipelines, but costly differentiable multi-bounce Monte Carlo (MC)…
Generative Image Inpainting with Segmentation Confusion Adversarial Training and Contrastive Learning
Zhiwen Zuo, Lei Zhao, Ailin Li +5
This paper presents a new adversarial training framework for image inpainting with segmentation confusion adversarial training (SCAT) and contrastive learning. SCAT plays an advers…
AesUST: Towards Aesthetic-Enhanced Universal Style Transfer
Zhizhong Wang, Zhanjie Zhang, Lei Zhao +4
Recent studies have shown remarkable success in universal style transfer which transfers arbitrary visual styles to content images. However, existing approaches suffer from the aes…