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Dual-MTGAN: Stochastic and Deterministic Motion Transfer for Image-to-Video Synthesis
Generating videos with content and motion variations is a challenging ta...
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Deep Representation Decomposition for Feature Disentanglement
Representation disentanglement aims at learning interpretable features, ...
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Semantics-Guided Representation Learning with Applications to Visual Synthesis
Learning interpretable and interpolatable latent representations has bee...
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Domain Generalized Person Re-Identification via Cross-Domain Episodic Learning
Aiming at recognizing images of the same person across distinct camera v...
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Semantics-Guided Clustering with Deep Progressive Learning for Semi-Supervised Person Re-identification
Person re-identification (re-ID) requires one to match images of the sam...
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Learning to Learn in a Semi-Supervised Fashion
To address semi-supervised learning from both labeled and unlabeled data...
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Wavelet Channel Attention Module with a Fusion Network for Single Image Deraining
Single image deraining is a crucial problem because rain severely degene...
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Transforming Multi-Concept Attention into Video Summarization
Video summarization is among challenging tasks in computer vision, which...
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Transfoming Multi-Concept Attention into Video Summarization
Video summarization is among challenging tasks in computer vision, which...
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Cross-Resolution Adversarial Dual Network for Person Re-Identification and Beyond
Person re-identification (re-ID) aims at matching images of the same per...
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Cross-Dataset Person Re-Identification via Unsupervised Pose Disentanglement and Adaptation
Person re-identification (re-ID) aims at recognizing the same person fro...
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Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification
Person re-identification (re-ID) aims at matching images of the same ide...
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Spatially and Temporally Efficient Non-local Attention Network for Video-based Person Re-Identification
Video-based person re-identification (Re-ID) aims at matching video sequ...
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Learning Resolution-Invariant Deep Representations for Person Re-Identification
Person re-identification (re-ID) solves the task of matching images acro...
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A Closer Look at Few-shot Classification
Few-shot classification aims to learn a classifier to recognize unseen c...
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Dual-modality seq2seq network for audio-visual event localization
Audio-visual event localization requires one to identify theevent which ...
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3D Shape Reconstruction from a Single 2D Image via 2D-3D Self-Consistency
Aiming at inferring 3D shapes from 2D images, 3D shape reconstruction ha...
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A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation
We present a novel and unified deep learning framework which is capable ...
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Deep Reinforcement Learning for Playing 2.5D Fighting Games
Deep reinforcement learning has shown its success in game playing. Howev...
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Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification
Person re-identification (Re-ID) aims at recognizing the same person fro...
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For Your Eyes Only: Learning to Summarize First-Person Videos
With the increasing amount of video data, it is desirable to highlight o...
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Multi-Label Zero-Shot Learning with Structured Knowledge Graphs
In this paper, we propose a novel deep learning architecture for multi-l...
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Order-Free RNN with Visual Attention for Multi-Label Classification
In this paper, we propose the joint learning attention and recurrent neu...
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Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation
While representation learning aims to derive interpretable features for ...
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No More Discrimination: Cross City Adaptation of Road Scene Segmenters
Despite the recent success of deep-learning based semantic segmentation,...
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