67 citations · 330 across the 26 of their papers we have counts for
6 papers · 1 filter
Zero-Shot Learning via Latent Space Encoding
Yunlong Yu, Zhong Ji, Jichang Guo +2
Zero-Shot Learning (ZSL) is typically achieved by resorting to a class semantic embedding space to transfer the knowledge from the seen classes to unseen ones. Capturing the common…
Video Summarization with Attention-Based Encoder-Decoder Networks
Zhong Ji, Kailin Xiong, Yanwei Pang +1
This paper addresses the problem of supervised video summarization by formulating it as a sequence-to-sequence learning problem, where the input is a sequence of original video fra…
Query-Aware Sparse Coding for Multi-Video Summarization
Zhong Ji, Yaru Ma, Yanwei Pang +1
Given the explosive growth of online videos, it is becoming increasingly important to relieve the tedious work of browsing and managing the video content of interest. Video summari…
Semantic Softmax Loss for Zero-Shot Learning
Zhong Ji, Yunxin Sun, Yulong Yu +2
A typical pipeline for Zero-Shot Learning (ZSL) is to integrate the visual features and the class semantic descriptors into a multimodal framework with a linear or bilinear model.…
Transductive Zero-Shot Learning with Adaptive Structural Embedding
Yunlong Yu, Zhong Ji, Jichang Guo +1
Zero-shot learning (ZSL) endows the computer vision system with the inferential capability to recognize instances of a new category that has never seen before. Two fundamental chal…
Transductive Zero-Shot Learning with a Self-training dictionary approach
Yunlong Yu, Zhong Ji, Xi Li +4
As an important and challenging problem in computer vision, zero-shot learning (ZSL) aims at automatically recognizing the instances from unseen object classes without training dat…