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09/01/2023
Fine-grained Recognition with Learnable Semantic Data Augmentation
Fine-grained image recognition is a longstanding computer vision challen...
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08/27/2023
Computation-efficient Deep Learning for Computer Vision: A Survey
Over the past decade, deep learning models have exhibited considerable a...
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07/16/2023
Sampling Proper Colorings on Line Graphs Using (1+o(1))Δ Colors
We prove that the single-site Glauber dynamics for sampling proper q-col...
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06/20/2023
Dynamic Perceiver for Efficient Visual Recognition
Early exiting has become a promising approach to improving the inference...
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03/14/2023
Adaptive Rotated Convolution for Rotated Object Detection
Rotated object detection aims to identify and locate objects in images w...
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12/08/2022
Deep Model Assembling
Large deep learning models have achieved remarkable success in many scen...
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11/17/2022
EfficientTrain: Exploring Generalized Curriculum Learning for Training Visual Backbones
The superior performance of modern deep networks usually comes at the pr...
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09/27/2022
AdaFocusV3: On Unified Spatial-temporal Dynamic Video Recognition
Recent research has revealed that reducing the temporal and spatial redu...
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08/02/2022
Making the Best of Both Worlds: A Domain-Oriented Transformer for Unsupervised Domain Adaptation
Extensive studies on Unsupervised Domain Adaptation (UDA) have propelled...
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01/09/2022
Glance and Focus Networks for Dynamic Visual Recognition
Spatial redundancy widely exists in visual recognition tasks, i.e., disc...
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12/28/2021
AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video Recognition
Recent works have shown that the computational efficiency of video recog...
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11/25/2021
Exploiting Both Domain-specific and Invariant Knowledge via a Win-win Transformer for Unsupervised Domain Adaptation
Unsupervised Domain Adaptation (UDA) aims to transfer knowledge from a l...
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05/31/2021
Not All Images are Worth 16x16 Words: Dynamic Vision Transformers with Adaptive Sequence Length
Vision Transformers (ViT) have achieved remarkable success in large-scal...
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05/07/2021
Adaptive Focus for Efficient Video Recognition
In this paper, we explore the spatial redundancy in video recognition wi...
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04/09/2021
CondenseNet V2: Sparse Feature Reactivation for Deep Networks
Reusing features in deep networks through dense connectivity is an effec...
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03/23/2021
MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition
Real-world training data usually exhibits long-tailed distribution, wher...
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03/23/2021
Transferable Semantic Augmentation for Domain Adaptation
Domain adaptation has been widely explored by transferring the knowledge...
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02/09/2021
Dynamic Neural Networks: A Survey
Dynamic neural network is an emerging research topic in deep learning. C...
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01/26/2021
Revisiting Locally Supervised Learning: an Alternative to End-to-end Training
Due to the need to store the intermediate activations for back-propagati...
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10/11/2020
Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification
The accuracy of deep convolutional neural networks (CNNs) generally impr...
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07/21/2020
Regularizing Deep Networks with Semantic Data Augmentation
Data augmentation is widely known as a simple yet surprisingly effective...
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07/05/2020
Meta-Semi: A Meta-learning Approach for Semi-supervised Learning
Deep learning based semi-supervised learning (SSL) algorithms have led t...
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09/26/2019