ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning

1 code implementation • NeurIPS 2023 • Junguang Jiang, Baixu Chen, Junwei Pan, Ximei Wang, Liu Dapeng, Jie Jiang, Mingsheng Long

Auxiliary-Task Learning (ATL) aims to improve the performance of the target task by leveraging the knowledge obtained from related tasks.

Debiased Self-Training for Semi-Supervised Learning

1 code implementation • 15 Feb 2022 • Baixu Chen, Junguang Jiang, Ximei Wang, Pengfei Wan, Jianmin Wang, Mingsheng Long

Yet these datasets are time-consuming and labor-exhaustive to obtain on realistic tasks.

Object Recognition Scene Classification +2

Transferability in Deep Learning: A Survey

1 code implementation • 15 Jan 2022 • Junguang Jiang, Yang Shu, Jianmin Wang, Mingsheng Long

The success of deep learning algorithms generally depends on large-scale data, while humans appear to have inherent ability of knowledge transfer, by recognizing and applying relevant knowledge from previous learning experiences when encountering and solving unseen tasks.

Domain Adaptation Transfer Learning

Decoupled Adaptation for Cross-Domain Object Detection

2 code implementations • ICLR 2022 • Junguang Jiang, Baixu Chen, Jianmin Wang, Mingsheng Long

Besides, previous methods focused on category adaptation but ignored another important part for object detection, i. e., the adaptation on bounding box regression.

Domain Adaptation Object +3

Regressive Domain Adaptation for Unsupervised Keypoint Detection

2 code implementations • CVPR 2021 • Junguang Jiang, Yifei Ji, Ximei Wang, Yufeng Liu, Jianmin Wang, Mingsheng Long

First, based on our observation that the probability density of the output space is sparse, we introduce a spatial probability distribution to describe this sparsity and then use it to guide the learning of the adversarial regressor.

Domain Adaptation Keypoint Detection