4 citations · 11 across the 5 of their papers we have counts for
10 papers
Exploiting Correspondences with All-pairs Correlations for Multi-view Depth Estimation
Kai Cheng, Hao Chen, Wei Yin +2
Multi-view depth estimation plays a critical role in reconstructing and understanding the 3D world. Recent learning-based methods have made significant progress in it. However, mul…
Improving Monocular Visual Odometry Using Learned Depth
Libo Sun, Wei Yin, Enze Xie +3
Monocular visual odometry (VO) is an important task in robotics and computer vision. Thus far, how to build accurate and robust monocular VO systems that can work well in diverse s…
Retrieval Augmented Classification for Long-Tail Visual Recognition
Alexander Long, Wei Yin, Thalaiyasingam Ajanthan +6
We introduce Retrieval Augmented Classification (RAC), a generic approach to augmenting standard image classification pipelines with an explicit retrieval module. RAC consists of a…
Generic Perceptual Loss for Modeling Structured Output Dependencies
Yifan Liu, Hao Chen, Yu Chen +2
The perceptual loss has been widely used as an effective loss term in image synthesis tasks including image super-resolution, and style transfer. It was believed that the success l…
Virtual Normal: Enforcing Geometric Constraints for Accurate and Robust Depth Prediction
Wei Yin, Yifan Liu, Chunhua Shen
Monocular depth prediction plays a crucial role in understanding 3D scene geometry. Although recent methods have achieved impressive progress in terms of evaluation metrics such as…
Learning to Recover 3D Scene Shape from a Single Image
Wei Yin, Jianming Zhang, Oliver Wang +4
Despite significant progress in monocular depth estimation in the wild, recent state-of-the-art methods cannot be used to recover accurate 3D scene shape due to an unknown depth sh…