Timezone: »
Zero-shot learning (ZSL) aims to recognize unseen object classes without any training samples, which can be regarded as a form of transfer learning from seen classes to unseen ones. This is made possible by learning a projection between a feature space and a semantic space (e.g. attribute space). Key to ZSL is thus to learn a projection function that is robust against the often large domain gap between the seen and unseen classes. In this paper, we propose a novel ZSL model termed domain-invariant projection learning (DIPL). Our model has two novel components: (1) A domain-invariant feature self-reconstruction task is introduced to the seen/unseen class data, resulting in a simple linear formulation that casts ZSL into a min-min optimization problem. Solving the problem is non-trivial, and a novel iterative algorithm is formulated as the solver, with rigorous theoretic algorithm analysis provided. (2) To further align the two domains via the learned projection, shared semantic structure among seen and unseen classes is explored via forming superclasses in the semantic space. Extensive experiments show that our model outperforms the state-of-the-art alternatives by significant margins.
Author Information
An Zhao (Renmin University of China)
Mingyu Ding (Renmin University of China)
Jiechao Guan (Renmin University of China)
Zhiwu Lu (Renmin University of China)
Tao Xiang (Samsung AI Centre, Cambridge)
Ji-Rong Wen (Renmin University of China)
More from the Same Authors
-
2021 Spotlight: SOFT: Softmax-free Transformer with Linear Complexity »
Jiachen Lu · Jinghan Yao · Junge Zhang · Xiatian Zhu · Hang Xu · Weiguo Gao · Chunjing XU · Tao Xiang · Li Zhang -
2021 Poster: SOFT: Softmax-free Transformer with Linear Complexity »
Jiachen Lu · Jinghan Yao · Junge Zhang · Xiatian Zhu · Hang Xu · Weiguo Gao · Chunjing XU · Tao Xiang · Li Zhang -
2021 Poster: One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective »
Jiun Tian Hoe · Kam Woh Ng · Tianyu Zhang · Chee Seng Chan · Yi-Zhe Song · Tao Xiang -
2021 Poster: Compressed Video Contrastive Learning »
Yuqi Huo · Mingyu Ding · Haoyu Lu · Nanyi Fei · Zhiwu Lu · Ji-Rong Wen · Ping Luo -
2020 Poster: Scalable Graph Neural Networks via Bidirectional Propagation »
Ming Chen · Zhewei Wei · Bolin Ding · Yaliang Li · Ye Yuan · Xiaoyong Du · Ji-Rong Wen