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Found 4 papers, 3 papers with code
An Empirical Study of Training State-of-the-Art LiDAR Segmentation Models
In the rapidly evolving field of autonomous driving, precise segmentation of LiDAR data is crucial for understanding complex 3D environments.
Robust Depth Linear Error Decomposition with Double Total Variation and Nuclear Norm for Dynamic MRI Reconstruction
By adding linear image domain error analysis, the noise is reduced after under-sampled and DFT processing, and the anti-interference ability of the algorithm is enhanced.
Superpoint Transformer for 3D Scene Instance Segmentation
The key step in this framework is a novel query decoder with transformers that can capture the instance information through the superpoint cross-attention mechanism and generate the superpoint masks of the instances.
Ranked #5 on
3D Instance Segmentation
on ScanNet(v2)
DehazeNet: An End-to-End System for Single Image Haze Removal
The key to achieve haze removal is to estimate a medium transmission map for an input hazy image.
Ranked #7 on
Image Dehazing
on RS-Haze
