9 citations · 13 across the 4 of their papers we have counts for
6 papers
Sketch-based Normal Map Generation with Geometric Sampling
Yi He, Haoran Xie, Chao Zhang +2
Normal map is an important and efficient way to represent complex 3D models. A designer may benefit from the auto-generation of high quality and accurate normal maps from freehand…
DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning
Sheldon Fung, Xuequan Lu, Chao Zhang +1
Face deepfake detection has seen impressive results recently. Nearly all existing deep learning techniques for face deepfake detection are fully supervised and require labels durin…
Deep Patch-based Human Segmentation
Dongbo Zhang, Zheng Fang, Xuequan Lu +4
3D human segmentation has seen noticeable progress in re-cent years. It, however, still remains a challenge to date. In this paper, weintroduce a deep patch-based method for 3D hum…
SHX: Search History Driven Crossover for Real-Coded Genetic Algorithm
Takumi Nakane, Xuequan Lu, Chao Zhang
In evolutionary algorithms, genetic operators iteratively generate new offspring which constitute a potentially valuable set of search history. To boost the performance of crossove…
G2MF-WA: Geometric Multi-Model Fitting with Weakly Annotated Data
Chao Zhang, Xuequan Lu, Katsuya Hotta +1
In this paper we attempt to address the problem of geometric multi-model fitting with resorting to a few weakly annotated (WA) data points, which has been sparsely studied so far.…
Blur-Countering Keypoint Detection via Eigenvalue Asymmetry
Chao Zhang, Xuequan Lu, Takuya Akashi
Well-known corner or local extrema feature based detectors such as FAST and DoG have achieved noticeable successes. However, detecting keypoints in the presence of blur has remaine…