Search Results for author: Yang Zou

Found 14 papers, 8 papers with code

MotionInput v2.0 supporting DirectX: A modular library of open-source gesture-based machine learning and computer vision methods for interacting and controlling existing software with a webcam

no code implementations10 Aug 2021 Ashild Kummen, Guanlin Li, Ali Hassan, Teodora Ganeva, Qianying Lu, Robert Shaw, Chenuka Ratwatte, Yang Zou, Lu Han, Emil Almazov, Sheena Visram, Andrew Taylor, Neil J Sebire, Lee Stott, Yvonne Rogers, Graham Roberts, Dean Mohamedally

We also introduce a series of bespoke gesture recognition classifications as DirectInput triggers, including gestures for idle states, auto calibration, depth capture from a 2D RGB webcam stream and tracking of facial motions such as mouth motions, winking, and head direction with rotation.

Gesture Recognition

Privacy Analysis of Deep Learning in the Wild: Membership Inference Attacks against Transfer Learning

no code implementations10 Sep 2020 Yang Zou, Zhikun Zhang, Michael Backes, Yang Zhang

One major privacy attack in this domain is membership inference, where an adversary aims to determine whether a target data sample is part of the training set of a target ML model.

Transfer Learning

Hard Class Rectification for Domain Adaptation

1 code implementation8 Aug 2020 Yunlong Zhang, Changxing Jing, Huangxing Lin, Chaoqi Chen, Yue Huang, Xinghao Ding, Yang Zou

Second, we further consider that the predictions of target samples belonging to the hard class are vulnerable to perturbations.

Unsupervised Domain Adaptation

Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification

1 code implementation ECCV 2020 Yang Zou, Xiaodong Yang, Zhiding Yu, B. V. K. Vijaya Kumar, Jan Kautz

To this end, we propose a joint learning framework that disentangles id-related/unrelated features and enforces adaptation to work on the id-related feature space exclusively.

Person Re-Identification Unsupervised Domain Adaptation

Conservative Wasserstein Training for Pose Estimation

no code implementations ICCV 2019 Xiaofeng Liu, Yang Zou, Tong Che, Peng Ding, Ping Jia, Jane You, Kumar B. V. K

We propose to incorporate inter-class correlations in a Wasserstein training framework by pre-defining ($i. e.,$ using arc length of a circle) or adaptively learning the ground metric.

Pose Estimation

Deep Classification Network for Monocular Depth Estimation

no code implementations23 Oct 2019 Azeez Oluwafemi, Yang Zou, B. V. K. Vijaya Kumar

Monocular Depth Estimation is usually treated as a supervised and regression problem when it actually is very similar to semantic segmentation task since they both are fundamentally pixel-level classification tasks.

Classification General Classification +2

Confidence Regularized Self-Training

2 code implementations ICCV 2019 Yang Zou, Zhiding Yu, Xiaofeng Liu, B. V. K. Vijaya Kumar, Jinsong Wang

Recent advances in domain adaptation show that deep self-training presents a powerful means for unsupervised domain adaptation.

Image Classification Semantic Segmentation +2

Unsupervised Domain Adaptation via Calibrating Uncertainties

1 code implementation25 Jul 2019 Ligong Han, Yang Zou, Ruijiang Gao, Lezi Wang, Dimitris Metaxas

Unsupervised domain adaptation (UDA) aims at inferring class labels for unlabeled target domain given a related labeled source dataset.

Unsupervised Domain Adaptation

Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training

1 code implementation18 Oct 2018 Yang Zou, Zhiding Yu, B. V. K. Vijaya Kumar, Jinsong Wang

In this paper, we propose a novel UDA framework based on an iterative self-training procedure, where the problem is formulated as latent variable loss minimization, and can be solved by alternatively generating pseudo labels on target data and re-training the model with these labels.

Semantic Segmentation Synthetic-to-Real Translation +1

Simultaneous Edge Alignment and Learning

3 code implementations ECCV 2018 Zhiding Yu, Weiyang Liu, Yang Zou, Chen Feng, Srikumar Ramalingam, B. V. K. Vijaya Kumar, Jan Kautz

Edge detection is among the most fundamental vision problems for its role in perceptual grouping and its wide applications.

Edge Detection Representation Learning

Scale Optimization for Full-Image-CNN Vehicle Detection

no code implementations20 Feb 2018 Yang Gao, Shouyan Guo, Kaimin Huang, Jiaxin Chen, Qian Gong, Yang Zou, Tong Bai, Gary Overett

By selecting better scales in the region proposal input and by combining feature maps through careful design of the convolutional neural network, we improve performance on smaller objects.

Object Detection Region Proposal

Sliced Wasserstein Kernels for Probability Distributions

no code implementations CVPR 2016 Soheil Kolouri, Yang Zou, Gustavo K. Rohde

Optimal transport distances, otherwise known as Wasserstein distances, have recently drawn ample attention in computer vision and machine learning as a powerful discrepancy measure for probability distributions.

Cannot find the paper you are looking for? You can Submit a new open access paper.