42 citations · 60 across the 8 of their papers we have counts for
8 papers
Unsupervised Recognition of Unknown Objects for Open-World Object Detection
Ruohuan Fang, Guansong Pang, Lei Zhou +2
Open-World Object Detection (OWOD) extends object detection problem to a realistic and dynamic scenario, where a detection model is required to be capable of detecting both known a…
Learning Adversarial Semantic Embeddings for Zero-Shot Recognition in Open Worlds
Tianqi Li, Guansong Pang, Xiao Bai +3
Zero-Shot Learning (ZSL) focuses on classifying samples of unseen classes with only their side semantic information presented during training. It cannot handle real-life, open-worl…
Learning Prototype via Placeholder for Zero-shot Recognition
Zaiquan Yang, Yang Liu, Wenjia Xu +3
Zero-shot learning (ZSL) aims to recognize unseen classes by exploiting semantic descriptions shared between seen classes and unseen classes. Current methods show that it is effect…
Goal-Oriented Gaze Estimation for Zero-Shot Learning
Yang Liu, Lei Zhou, Xiao Bai +4
Zero-shot learning (ZSL) aims to recognize novel classes by transferring semantic knowledge from seen classes to unseen classes. Since semantic knowledge is built on attributes sha…
Information Bottleneck Constrained Latent Bidirectional Embedding for Zero-Shot Learning
Yang Liu, Lei Zhou, Xiao Bai +3
Zero-shot learning (ZSL) aims to recognize novel classes by transferring semantic knowledge from seen classes to unseen classes. Though many ZSL methods rely on a direct mapping be…
A One-step Pruning-recovery Framework for Acceleration of Convolutional Neural Networks
Dong Wang, Lei Zhou, Xiao Bai +1
Acceleration of convolutional neural network has received increasing attention during the past several years. Among various acceleration techniques, filter pruning has its inherent…
Exploring Linear Relationship in Feature Map Subspace for ConvNets Compression
Dong Wang, Lei Zhou, Xueni Zhang +2
While the research on convolutional neural networks (CNNs) is progressing quickly, the real-world deployment of these models is often limited by computing resources and memory cons…
Fast Subspace Clustering Based on the Kronecker Product
Lei Zhou, Xiao Bai, Xianglong Liu +2
Subspace clustering is a useful technique for many computer vision applications in which the intrinsic dimension of high-dimensional data is often smaller than the ambient dimensio…