4 citations · 6 across the 4 of their papers we have counts for
6 papers
Multi-resolution Monocular Depth Map Fusion by Self-supervised Gradient-based Composition
Yaqiao Dai, Renjiao Yi, Chenyang Zhu +2
Monocular depth estimation is a challenging problem on which deep neural networks have demonstrated great potential. However, depth maps predicted by existing deep models usually l…
6DOF Pose Estimation of a 3D Rigid Object based on Edge-enhanced Point Pair Features
Chenyi Liu, Fei Chen, Lu Deng +5
The point pair feature (PPF) is widely used for 6D pose estimation. In this paper, we propose an efficient 6D pose estimation method based on the PPF framework. We introduce a well…
DisARM: Displacement Aware Relation Module for 3D Detection
Yao Duan, Chenyang Zhu, Yuqing Lan +3
We introduce Displacement Aware Relation Module (DisARM), a novel neural network module for enhancing the performance of 3D object detection in point cloud scenes. The core idea of…
Leveraging Multi-view Image Sets for Unsupervised Intrinsic Image Decomposition and Highlight Separation
Renjiao Yi, Ping Tan, Stephen Lin
We present an unsupervised approach for factorizing object appearance into highlight, shading, and albedo layers, trained by multi-view real images. To do so, we construct a multi-…
SCORES: Shape Composition with Recursive Substructure Priors
Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri +2
We introduce SCORES, a recursive neural network for shape composition. Our network takes as input sets of parts from two or more source 3D shapes and a rough initial placement of t…
Faces as Lighting Probes via Unsupervised Deep Highlight Extraction
Renjiao Yi, Chenyang Zhu, Ping Tan +1
We present a method for estimating detailed scene illumination using human faces in a single image. In contrast to previous works that estimate lighting in terms of low-order basis…