Search Results for author: Luyu Yang

Found 6 papers, 2 papers with code

Curriculum Manager for Source Selection in Multi-Source Domain Adaptation

no code implementations ECCV 2020 Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava

In this paper, we proposed an adversarial agent that learns a dynamic curriculum for source samples, called Curriculum Manager for Source Selection (CMSS).

Multi-Source Unsupervised Domain Adaptation Unsupervised Domain Adaptation

Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation

1 code implementation ICCV 2021 Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim

To integrate the strengths of the two classifiers, we apply the well-established co-training framework, in which the two classifiers exchange their high confident predictions to iteratively "teach each other" so that both classifiers can excel in the target domain.

Semi-supervised Domain Adaptation Unsupervised Domain Adaptation

Burn After Reading: Online Adaptation for Cross-domain Streaming Data

no code implementations8 Dec 2021 Luyu Yang, Mingfei Gao, Zeyuan Chen, ran Xu, Abhinav Shrivastava, Chetan Ramaiah

In the context of online privacy, many methods propose complex privacy and security preserving measures to protect sensitive data.

Unsupervised Domain Adaptation

Learning Semantic Correspondence with Sparse Annotations

1 code implementation15 Aug 2022 Shuaiyi Huang, Luyu Yang, Bo He, Songyang Zhang, Xuming He, Abhinav Shrivastava

In this paper, we aim to address the challenge of label sparsity in semantic correspondence by enriching supervision signals from sparse keypoint annotations.

Denoising Semantic correspondence

Are Dense Labels Always Necessary for 3D Object Detection from Point Cloud?

no code implementations5 Mar 2024 Chenqiang Gao, Chuandong Liu, Jun Shu, Fangcen Liu, Jiang Liu, Luyu Yang, Xinbo Gao, Deyu Meng

Current state-of-the-art (SOTA) 3D object detection methods often require a large amount of 3D bounding box annotations for training.

3D Object Detection object-detection +1

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