3 citations · 7 across the 7 of their papers we have counts for
7 papers
AbsGS: Recovering Fine Details for 3D Gaussian Splatting
Zongxin Ye, Wenyu Li, Sidun Liu +2
3D Gaussian Splatting (3D-GS) technique couples 3D Gaussian primitives with differentiable rasterization to achieve high-quality novel view synthesis results while providing advanc…
TFDMNet: A Novel Network Structure Combines the Time Domain and Frequency Domain Features
Hengyue Pan, Yixin Chen, Zhiliang Tian +3
Convolutional neural network (CNN) has achieved impressive success in computer vision during the past few decades. The image convolution operation helps CNNs to get good performanc…
Rethinking SIGN Training: Provable Nonconvex Acceleration without First- and Second-Order Gradient Lipschitz
Tao Sun, Congliang Chen, Peng Qiao +3
Sign-based stochastic methods have gained attention due to their ability to achieve robust performance despite using only the sign information for parameter updates. However, the c…
PVP: Pre-trained Visual Parameter-Efficient Tuning
Zhao Song, Ke Yang, Naiyang Guan +3
Large-scale pre-trained transformers have demonstrated remarkable success in various computer vision tasks. However, it is still highly challenging to fully fine-tune these models…
Towards Vision Transformer Unrolling Fixed-Point Algorithm: a Case Study on Image Restoration
Peng Qiao, Sidun Liu, Tao Sun +2
The great success of Deep Neural Networks (DNNs) has inspired the algorithmic development of DNN-based Fixed-Point (DNN-FP) for computer vision tasks. DNN-FP methods, trained by Ba…
Multi-Outputs Is All You Need For Deblur
Sidun Liu, Peng Qiao, Yong Dou
Image deblurring task is an ill-posed one, where exists infinite feasible solutions for blurry image. Modern deep learning approaches usually discard the learning of blur kernels a…