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09/02/2023
Big-model Driven Few-shot Continual Learning
Few-shot continual learning (FSCL) has attracted intensive attention and...
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04/14/2021
Global Information Guided Video Anomaly Detection
Video anomaly detection (VAD) is currently a challenging task due to the...
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09/30/2020
Attention-Aware Noisy Label Learning for Image Classification
Deep convolutional neural networks (CNNs) learned on large-scale labeled...
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09/03/2020
Spatial Transformer Point Convolution
Point clouds are unstructured and unordered in the embedded 3D space. In...
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08/20/2020
Localizing Anomalies from Weakly-Labeled Videos
Video anomaly detection under video-level labels is currently a challeng...
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06/08/2019
Pattern-Affinitive Propagation across Depth, Surface Normal and Semantic Segmentation
In this paper, we propose a novel Pattern-Affinitive Propagation (PAP) f...
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11/11/2018
Gaussian-Induced Convolution for Graphs
Learning representation on graph plays a crucial role in numerous tasks ...
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09/11/2018
Context-Dependent Diffusion Network for Visual Relationship Detection
Visual relationship detection can bridge the gap between computer vision...
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07/07/2018
When Work Matters: Transforming Classical Network Structures to Graph CNN
Numerous pattern recognition applications can be formed as learning from...
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04/16/2018
Walk-Steered Convolution for Graph Classification
Graph classification is a fundamental but challenging problem due to the...
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02/27/2018
Spatio-Temporal Graph Convolution for Skeleton Based Action Recognition
Variations of human body skeletons may be considered as dynamic graphs, ...
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11/17/2017
Action-Attending Graphic Neural Network
The motion analysis of human skeletons is crucial for human action recog...
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08/07/2017
MemNet: A Persistent Memory Network for Image Restoration
Recently, very deep convolutional neural networks (CNNs) have been attra...
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12/22/2015
Deep Learning with S-shaped Rectified Linear Activation Units
Rectified linear activation units are important components for state-of-...
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12/06/2014
