Search Results for author:
Found 4 papers, 2 papers with code
HiDiffusion: Unlocking Higher-Resolution Creativity and Efficiency in Pretrained Diffusion Models
Extensive experiments demonstrate that our approach can address object duplication and heavy computation issues, achieving state-of-the-art performance on higher-resolution image synthesis tasks.
Boosting Semi-Supervised Learning by Exploiting All Unlabeled Data
ANL introduces the additional negative pseudo-label for all unlabeled data to leverage low-confidence examples.
GeoGCN: Geometric Dual-domain Graph Convolution Network for Point Cloud Denoising
We propose GeoGCN, a novel geometric dual-domain graph convolution network for point cloud denoising (PCD).
Lane Detection in Low-light Conditions Using an Efficient Data Enhancement : Light Conditions Style Transfer
Nowadays, deep learning techniques are widely used for lane detection, but application in low-light conditions remains a challenge until this day.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
