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Found 6 papers, 6 papers with code
PointHR: Exploring High-Resolution Architectures for 3D Point Cloud Segmentation
Significant progress has been made recently in point cloud segmentation utilizing an encoder-decoder framework, which initially encodes point clouds into low-resolution representations and subsequently decodes high-resolution predictions.
Ranked #5 on
Semantic Segmentation
on ScanNet
Collect-and-Distribute Transformer for 3D Point Cloud Analysis
In this paper, we propose a new transformer network equipped with a collect-and-distribute mechanism to communicate short- and long-range contexts of point clouds, which we refer to as CDFormer.
GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentation
However, recent projection-based methods for point cloud semantic segmentation usually utilize a vanilla late fusion strategy for the predictions of different views, failing to explore the complementary information from a geometric perspective during the representation learning.
Ranked #1 on
Robust 3D Semantic Segmentation
on nuScenes-C
End2End Occluded Face Recognition by Masking Corrupted Features
However, the state-of-the-art general face recognition models do not generalize well to occluded face images, which are exactly the common cases in real-world scenarios.
SynFace: Face Recognition with Synthetic Data
We then analyze the underlying causes behind the performance gap, e. g., the poor intra-class variations and the domain gap between synthetic and real face images.
Cross View Fusion for 3D Human Pose Estimation
It consists of two separate steps: (1) estimating the 2D poses in multi-view images and (2) recovering the 3D poses from the multi-view 2D poses.
Ranked #6 on
3D Human Pose Estimation
on Total Capture
