6 citations · 8 across the 6 of their papers we have counts for
8 papers
SCHEME: Scalable Channel Mixer for Vision Transformers
Deepak Sridhar, Yunsheng Li, Nuno Vasconcelos
Vision Transformers have achieved impressive performance in many vision tasks. While the token mixer or attention block has been studied in great detail, much less research has bee…
Dense Network Expansion for Class Incremental Learning
Zhiyuan Hu, Yunsheng Li, Jiancheng Lyu +2
The problem of class incremental learning (CIL) is considered. State-of-the-art approaches use a dynamic architecture based on network expansion (NE), in which a task expert is add…
Dynamic Transfer for Multi-Source Domain Adaptation
Yunsheng Li, Lu Yuan, Yinpeng Chen +2
Recent works of multi-source domain adaptation focus on learning a domain-agnostic model, of which the parameters are static. However, such a static model is difficult to handle co…
Deep Hashing with Hash-Consistent Large Margin Proxy Embeddings
Pedro Morgado, Yunsheng Li, Jose Costa Pereira +2
Image hash codes are produced by binarizing the embeddings of convolutional neural networks (CNN) trained for either classification or retrieval. While proxy embeddings achieve goo…
Explainable Object-induced Action Decision for Autonomous Vehicles
Yiran Xu, Xiaoyin Yang, Lihang Gong +4
A new paradigm is proposed for autonomous driving. The new paradigm lies between the end-to-end and pipelined approaches, and is inspired by how humans solve the problem. While it…
Efficient Multi-Domain Network Learning by Covariance Normalization
Yunsheng Li, Nuno Vasconcelos
The problem of multi-domain learning of deep networks is considered. An adaptive layer is induced per target domain and a novel procedure, denoted covariance normalization (CovNorm…
Semantic Fisher Scores for Task Transfer: Using Objects to Classify Scenes
Mandar Dixit, Yunsheng Li, Nuno Vasconcelos
The transfer of a neural network (CNN) trained to recognize objects to the task of scene classification is considered. A Bag-of-Semantics (BoS) representation is first induced, by…
Bidirectional Learning for Domain Adaptation of Semantic Segmentation
Yunsheng Li, Lu Yuan, Nuno Vasconcelos
Domain adaptation for semantic image segmentation is very necessary since manually labeling large datasets with pixel-level labels is expensive and time consuming. Existing domain…