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Found 5 papers, 3 papers with code
MUC: Mixture of Uncalibrated Cameras for Robust 3D Human Body Reconstruction
Next, instead of simply averaging models across views, we train a network to determine the weights of individual views for their fusion, based on the parameters estimated for joints and hands of human body as well as camera positions.
DR2: Diffusion-based Robust Degradation Remover for Blind Face Restoration
However, it is expensive and infeasible to include every type of degradation to cover real-world cases in the training data.
Object as Hotspots: An Anchor-Free 3D Object Detection Approach via Firing of Hotspots
Accurate 3D object detection in LiDAR based point clouds suffers from the challenges of data sparsity and irregularities.
Ranked #3 on
3D Object Detection
on KITTI Pedestrians Moderate
Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detection
We also propose component variants of F-ConvNet, including an FCN variant that extracts multi-resolution frustum features, and a refined use of F-ConvNet over a reduced 3D space.
Ranked #3 on
3D Object Detection
on KITTI Cyclists Easy
Part-Aware Fine-grained Object Categorization using Weakly Supervised Part Detection Network
In this work, we propose a Weakly Supervised Part Detection Network (PartNet) that is able to detect discriminative local parts for use of fine-grained categorization.
