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Directional Statistics-based Deep Metric Learning for Image Classification and Retrieval
High-Fidelity 3D Digital Human Head Creation from RGB-D Selfies
- Linchao Bao, Xiangkai Lin, Zhengyou Zhang
- Computer ScienceACM Transactions on Graphics
- 12 October 2020
A new facial geometry modeling and reflectance synthesis procedure that significantly improves the state of the art and combines parametric fitting and Convolutional Neural Networks to synthesize high-resolution albedo/normal maps with realistic hair/pore/wrinkle details.
Animatable Neural Radiance Fields from Monocular RGB Video
- Jianchuan Chen, Ying Zhang, Di Kang, Xuefei Zhe, Linchao Bao, Huchuan Lu
- Computer ScienceArXiv
- 25 June 2021
The approach extends neural radiance fields (NeRF) to the dynamic scenes with human movements via introducing explicit pose-guided deformation while learning the scene representation network to compensate for inaccurate pose estimation.
Audio2Gestures: Generating Diverse Gestures from Speech Audio with Conditional Variational Autoencoders
- Jing Li, Di Kang, Linchao Bao
- Computer ScienceIEEE International Conference on Computer Vision
- 15 August 2021
A novel conditional variational autoencoder (VAE) that explicitly models one-to-many audio- to-motion mapping by splitting the cross-modal latent code into shared code and motion-specific code is proposed.
Model-based 3D Hand Reconstruction via Self-Supervised Learning
- Yujin Chen, Zhigang Tu, Junsong Yuan
- Computer ScienceComputer Vision and Pattern Recognition
- 22 March 2021
This work proposes S2HAND, a self-supervised 3D hand reconstruction network that can jointly estimate pose, shape, texture, and the camera viewpoint and utilizes the consistency between 2D and 3D representations and a set of novel losses to rationalize outputs of the neural network.
Semantic Hierarchy Preserving Deep Hashing for Large-Scale Image Retrieval
- Xuefei Zhe, Le Ou-Yang, Shifeng Chen, Hong Yan
- Computer Science17th International Conference on Machine Vision…
- 31 January 2019
This paper presents an effective algorithm to train a deep hashing model that can preserve a semantic hierarchy structure for large-scale image retrieval and achieves state-of-the-art results in terms of hierarchical retrieval.
REALY: Rethinking the Evaluation of 3D Face Reconstruction
- Zenghao Chai, Haoxian Zhang, Linchao Bao
- Computer ScienceEuropean Conference on Computer Vision
- 18 March 2022
A novel evaluation approach with a new benchmark REALY, consists of 100 globally aligned face scans with accurate facial keypoints, high-quality region masks, and topology-consistent meshes that performs region-wise shape alignment and leads to more accurate, bidirectional correspondences during computing the shape errors.
Deep Class-Wise Hashing: Semantics-Preserving Hashing via Class-Wise Loss
- Xuefei Zhe, Shifeng Chen, Hong Yan
- Computer ScienceIEEE Transactions on Neural Networks and Learning…
- 12 March 2018
This model is motivated by deep metric learning that directly takes semantic labels as supervised information in training and generates corresponding discriminant hashing code that preserves semantic variations while penalizes the overlapping part of different classes in the embedding space.
Deep center-based dual-constrained hashing for discriminative face image retrieval
Feature selection based on co-clustering for effective facial expression recognition
- Sheheryar Khan, Lijiang Chen, Xuefei Zhe, Hong Yan
- Computer ScienceInternational Conference on Machine Learning and…
- 1 July 2016
A co-clustering based approach to the selection of distinguished and interpretable features to deal with the curse of dimensionality issue and it is illustrated that the selected features not only reduces the dimensionality but also identify the distinguishable face regions on images amongst all expressions.