Search Results for author:
Found 7 papers, 3 papers with code
Cross-Resolution Land Cover Classification Using Outdated Products and Transformers
In this paper, we propose a Transformerbased weakly supervised method for cross-resolution land cover classification using outdated data.
RainDiffusion: When Unsupervised Learning Meets Diffusion Models for Real-world Image Deraining
Before answering it, we observe two major obstacles of diffusion models in real-world image deraining: the need for paired training data and the limited utilization of multi-scale rain patterns.
ImLiDAR: Cross-Sensor Dynamic Message Propagation Network for 3D Object Detection
We propose ImLiDAR, a new 3OD paradigm to narrow the cross-sensor discrepancies by progressively fusing the multi-scale features of camera Images and LiDAR point clouds.
PSFormer: Point Transformer for 3D Salient Object Detection
We propose PSFormer, an effective point transformer model for 3D salient object detection.
Semi-MoreGAN: A New Semi-supervised Generative Adversarial Network for Mixture of Rain Removal
Rain is one of the most common weather which can completely degrade the image quality and interfere with the performance of many computer vision tasks, especially under heavy rain conditions.
Detail-recovery Image Deraining via Dual Sample-augmented Contrastive Learning
To bridge the two domain gaps, we propose a semi-supervised detail-recovery image deraining network (Semi-DRDNet) with dual sample-augmented contrastive learning.
MBA-RainGAN: Multi-branch Attention Generative Adversarial Network for Mixture of Rain Removal from Single Images
We observe three intriguing phenomenons that, 1) rain is a mixture of raindrops, rain streaks and rainy haze; 2) the depth from the camera determines the degrees of object visibility, where objects nearby and faraway are visually blocked by rain streaks and rainy haze, respectively; and 3) raindrops on the glass randomly affect the object visibility of the whole image space.
