Renjiao Yi, Chenyang Zhu,
Ping Tan and Stephen Lin, "Faces as Lighting Probes via Unsupervised Deep Highlight Extraction", ECCV 2018.
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 functions or distant point lights, our technique estimates illumination at a higher precision in the form of a non-parametric environment map...
Arxiv (with supplementary material)   Codes   Poster   Bibtex
Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri, Renjiao Yi and Hao Zhang,
SCORES: Shape Composition with Recursive Substructure Priors", ACM Transactions on Graphics (SIGGRAPH Asia 2018).
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 the parts. It outputs an optimized part structure for the composed shape, leading to high-quality geometry construction. A unique feature of our composition network is that it is not merely learning how to connect parts. Our goal is to produce a coherent and plausible 3D shape...
Chenyang Zhu, Renjiao Yi,
Wallace Lira, Ibraheem Alhashim, Kai Xu and Hao Zhang, "Deformation-Driven Shape Correspondence via Shape Recognition", ACM Transactions on Graphics (SIGGRAPH 2017), 36(4): 51, 2017.
Many approaches to shape comparison and recognition start by establishing a shape correspondence. We "turn the table" and show that quality shape correspondences can be obtained by performing many shape recognition tasks. What is more, the method we develop computes a fine-grained, topology-varying part correspondence between two 3D shapes where the core evaluation mechanism only recognizes shapes globally...
Renjiao Yi, Jue Wang, Ping Tan , "Automatic Fence Segmentation in Videos of Dynamic Scenes", IEEE Conference on Computer Vision and Patten Recognition (CVPR), Las Vegas, USA, Jun. 2016.
We present a fully automatic approach to detect and segment fence-like occluders from a video clip. Unlike previous approaches that usually assume either static scenes or cameras, our method is capable of handling both dynamic scenes and moving cameras...