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20172023
most citedA Closer Look at Few-shot Classification

185 citations · 590 across the 29 of their papers we have counts for

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Showing 2017 · cs.CVShow all

5 papers · 2 filters

cs.CV2017

Summarizing First-Person Videos from Third Persons' Points of Views

Hsuan-I Ho, Wei-Chen Chiu, Yu-Chiang Frank Wang

Video highlight or summarization is among interesting topics in computer vision, which benefits a variety of applications like viewing, searching, or storage. However, most existin…

cs.CV2017

Multi-Label Zero-Shot Learning with Structured Knowledge Graphs

Chung-Wei Lee, Wei Fang, Chih-Kuan Yeh +1

In this paper, we propose a novel deep learning architecture for multi-label zero-shot learning (ML-ZSL), which is able to predict multiple unseen class labels for each input insta…

cs.CV2017★ 52 cited

Order-Free RNN with Visual Attention for Multi-Label Classification

Shang-Fu Chen, Yi-Chen Chen, Chih-Kuan Yeh +1

In this paper, we propose the joint learning attention and recurrent neural network (RNN) models for multi-label classification. While approaches based on the use of either model e…

cs.CV2017★ 1 cited

Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation

Yen-Cheng Liu, Yu-Ying Yeh, Tzu-Chien Fu +3

While representation learning aims to derive interpretable features for describing visual data, representation disentanglement further results in such features so that particular i…

cs.CV2017★ 23 cited

No More Discrimination: Cross City Adaptation of Road Scene Segmenters

Yi-Hsin Chen, Wei-Yu Chen, Yu-Ting Chen +3

Despite the recent success of deep-learning based semantic segmentation, deploying a pre-trained road scene segmenter to a city whose images are not presented in the training set w…