233 citations · 596 across the 12 of their papers we have counts for
12 papers
Self-Supervised Monocular Depth Estimation: Solving the Edge-Fattening Problem
Xingyu Chen, Ruonan Zhang, Ji Jiang +3
Self-supervised monocular depth estimation (MDE) models universally suffer from the notorious edge-fattening issue. Triplet loss, as a widespread metric learning strategy, has larg…
Neural Surface Reconstruction of Dynamic Scenes with Monocular RGB-D Camera
Hongrui Cai, Wanquan Feng, Xuetao Feng +2
We propose Neural-DynamicReconstruction (NDR), a template-free method to recover high-fidelity geometry and motions of a dynamic scene from a monocular RGB-D camera. In NDR, we ado…
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize
Yan Wang, Xiangyu Chen, Yurong You +5
In the domain of autonomous driving, deep learning has substantially improved the 3D object detection accuracy for LiDAR and stereo camera data alike. While deep networks are great…
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection
Rui Qian, Divyansh Garg, Yan Wang +6
Reliable and accurate 3D object detection is a necessity for safe autonomous driving. Although LiDAR sensors can provide accurate 3D point cloud estimates of the environment, they…
SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning
Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger +1
Few-shot learners aim to recognize new object classes based on a small number of labeled training examples. To prevent overfitting, state-of-the-art few-shot learners use meta-lear…
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images
Brian H. Wang, Wei-Lun Chao, Yan Wang +3
Object segmentation in three-dimensional (3-D) point clouds is a critical task for robots capable of 3-D perception. Despite the impressive performance of deep learning-based appro…