4 citations · 5 across the 6 of their papers we have counts for
6 papers · 1 filter
PNeSM: Arbitrary 3D Scene Stylization via Prompt-Based Neural Style Mapping
Jiafu Chen, Wei Xing, Jiakai Sun +7
3D scene stylization refers to transform the appearance of a 3D scene to match a given style image, ensuring that images rendered from different viewpoints exhibit the same style a…
CEAT: Continual Expansion and Absorption Transformer for Non-Exemplar Class-Incremental Learning
Xinyuan Gao, Songlin Dong, Yuhang He +2
In real-world applications, dynamic scenarios require the models to possess the capability to learn new tasks continuously without forgetting the old knowledge. Experience-Replay m…
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…
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…
SOIT: Segmenting Objects with Instance-Aware Transformers
Xiaodong Yu, Dahu Shi, Xing Wei +3
This paper presents an end-to-end instance segmentation framework, termed SOIT, that Segments Objects with Instance-aware Transformers. Inspired by DETR \cite{carion2020end}, our m…
Texture Reformer: Towards Fast and Universal Interactive Texture Transfer
Zhizhong Wang, Lei Zhao, Haibo Chen +4
In this paper, we present the texture reformer, a fast and universal neural-based framework for interactive texture transfer with user-specified guidance. The challenges lie in thr…