Search Results for author: Yue He

Found 13 papers, 7 papers with code

StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learning

no code implementations CVPR 2022 Yi-Hua Huang, Yue He, Yu-Jie Yuan, Yu-Kun Lai, Lin Gao

We first pre-train a standard NeRF of the 3D scene to be stylized and replace its color prediction module with a style network to obtain a stylized NeRF.

Image Stylization

NICO++: Towards Better Benchmarking for Domain Generalization

1 code implementation17 Apr 2022 Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui

Most current evaluation methods for domain generalization (DG) adopt the leave-one-out strategy as a compromise on the limited number of domains.

Domain Generalization Generalization Bounds +1

The Gerber-Shiu discounted penalty function: From practical perspectives

no code implementations21 Mar 2022 Yue He, Reiichiro Kawai, Yasutaka Shimizu, Kazutoshi Yamazaki

The Gerber-Shiu function provides a unified framework for the evaluation of a variety of risk quantities.

CausPref: Causal Preference Learning for Out-of-Distribution Recommendation

1 code implementation8 Feb 2022 Yue He, Zimu Wang, Peng Cui, Hao Zou, Yafeng Zhang, Qiang Cui, Yong Jiang

In spite of the tremendous development of recommender system owing to the progressive capability of machine learning recently, the current recommender system is still vulnerable to the distribution shift of users and items in realistic scenarios, leading to the sharp decline of performance in testing environments.

Recommendation Systems

Visual Semantics Allow for Textual Reasoning Better in Scene Text Recognition

1 code implementation AAAI 2022 2021 Yue He, Chen Chen, Jing Zhang, Juhua Liu, Fengxiang He, Chaoyue Wang, Bo Du

Technically, given the character segmentation maps predicted by a VR model, we construct a subgraph for each instance, where nodes represent the pixels in it and edges are added between nodes based on their spatial similarity.

Ranked #2 on Scene Text Recognition on SVTP (using extra training data)

Language Modelling Scene Text Recognition

Towards Out-Of-Distribution Generalization: A Survey

no code implementations31 Aug 2021 Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui

Classic machine learning methods are built on the $i. i. d.$ assumption that training and testing data are independent and identically distributed.

Out-of-Distribution Generalization Representation Learning

Good Practices and A Strong Baseline for Traffic Anomaly Detection

1 code implementation9 May 2021 Yuxiang Zhao, Wenhao Wu, Yue He, YingYing Li, Xiao Tan, Shifeng Chen

In this paper, we propose a straightforward and efficient framework that includes pre-processing, a dynamic track module, and post-processing.

Anomaly Detection Management +1

Deep Stable Learning for Out-Of-Distribution Generalization

1 code implementation CVPR 2021 Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen

Approaches based on deep neural networks have achieved striking performance when testing data and training data share similar distribution, but can significantly fail otherwise.

Domain Generalization Out-of-Distribution Generalization

Sample Balancing for Improving Generalization under Distribution Shifts

no code implementations1 Jan 2021 Xingxuan Zhang, Peng Cui, Renzhe Xu, Yue He, Linjun Zhou, Zheyan Shen

We propose to address this problem by removing the dependencies between features via reweighting training samples, which results in a more balanced distribution and helps deep models get rid of spurious correlations and, in turn, concentrate more on the true connection between features and labels.

Domain Adaptation Object Recognition

Counterfactual Prediction for Bundle Treatment

no code implementations NeurIPS 2020 Hao Zou, Peng Cui, Bo Li, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He

Estimating counterfactual outcome of different treatments from observational data is an important problem to assist decision making in a variety of fields.

Decision Making Marketing +1

One-shot Face Reenactment

1 code implementation5 Aug 2019 Yunxuan Zhang, Siwei Zhang, Yue He, Cheng Li, Chen Change Loy, Ziwei Liu

However, in real-world scenario end-users often only have one target face at hand, rendering existing methods inapplicable.

Face Reconstruction Face Reenactment

Towards Non-I.I.D. Image Classification: A Dataset and Baselines

no code implementations7 Jun 2019 Yue He, Zheyan Shen, Peng Cui

The experimental results demonstrate that NICO can well support the training of ConvNet model from scratch, and a batch balancing module can help ConvNets to perform better in Non-I. I. D.

Classification General Classification +1

Merge or Not? Learning to Group Faces via Imitation Learning

1 code implementation13 Jul 2017 Yue He, Kaidi Cao, Cheng Li, Chen Change Loy

Given a large number of unlabeled face images, face grouping aims at clustering the images into individual identities present in the data.

Imitation Learning

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