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09/04/2023
Leveraging Reward Consistency for Interpretable Feature Discovery in Reinforcement Learning
The black-box nature of deep reinforcement learning (RL) hinders them fr...
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09/04/2023
Hundreds Guide Millions: Adaptive Offline Reinforcement Learning with Expert Guidance
Offline reinforcement learning (RL) optimizes the policy on a previously...
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09/04/2023
DAT++: Spatially Dynamic Vision Transformer with Deformable Attention
Transformers have shown superior performance on various vision tasks. Th...
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08/30/2023
Latency-aware Unified Dynamic Networks for Efficient Image Recognition
Dynamic computation has emerged as a promising avenue to enhance the inf...
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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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08/08/2023
Learning Specialized Activation Functions for Physics-informed Neural Networks
Physics-informed neural networks (PINNs) are known to suffer from optimi...
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08/01/2023
FLatten Transformer: Vision Transformer using Focused Linear Attention
The quadratic computation complexity of self-attention has been a persis...
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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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06/08/2023
Offline Prioritized Experience Replay
Offline reinforcement learning (RL) is challenged by the distributional ...
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06/06/2023
Boosting Offline Reinforcement Learning with Action Preference Query
Training practical agents usually involve offline and online reinforceme...
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04/09/2023
Slide-Transformer: Hierarchical Vision Transformer with Local Self-Attention
Self-attention mechanism has been a key factor in the recent progress of...
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04/06/2023
Zero-shot Generative Model Adaptation via Image-specific Prompt Learning
Recently, CLIP-guided image synthesis has shown appealing performance on...
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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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01/18/2023
Joint Representation Learning for Text and 3D Point Cloud
Recent advancements in vision-language pre-training (e.g. CLIP) have sho...
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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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11/17/2022
Cross-Modal Adapter for Text-Video Retrieval
Text-video retrieval is an important multi-modal learning task, where th...
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10/17/2022
Contrastive Language-Image Pre-Training with Knowledge Graphs
Recent years have witnessed the fast development of large-scale pre-trai...
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10/12/2022
Efficient Knowledge Distillation from Model Checkpoints
Knowledge distillation is an effective approach to learn compact models ...
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10/12/2022
Latency-aware Spatial-wise Dynamic Networks
Spatial-wise dynamic convolution has become a promising approach to impr...
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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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09/18/2022
ActiveNeRF: Learning where to See with Uncertainty Estimation
Recently, Neural Radiance Fields (NeRF) has shown promising performances...
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09/17/2022
Learning to Weight Samples for Dynamic Early-exiting Networks
Early exiting is an effective paradigm for improving the inference effic...
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07/04/2022
The Neural-Prediction based Acceleration Algorithm of Column Generation for Graph-Based Set Covering Problems
Set covering problem is an important class of combinatorial optimization...
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03/16/2022
Pseudo-Q: Generating Pseudo Language Queries for Visual Grounding
Visual grounding, i.e., localizing objects in images according to natura...
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02/25/2022
Learn From the Past: Experience Ensemble Knowledge Distillation
Traditional knowledge distillation transfers "dark knowledge" of a pre-t...
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02/14/2022
Domain Adaptation via Prompt Learning
Unsupervised domain adaption (UDA) aims to adapt models learned from a w...
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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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01/03/2022
Vision Transformer with Deformable Attention
Transformers have recently shown superior performances on various vision...
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12/09/2021
Exploring the Equivalence of Siamese Self-Supervised Learning via A Unified Gradient Framework
Self-supervised learning has shown its great potential to extract powerf...
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12/06/2021
Temporal-Spatial Causal Interpretations for Vision-Based Reinforcement Learning
Deep reinforcement learning (RL) agents are becoming increasingly profic...
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11/29/2021
On the Integration of Self-Attention and Convolution
Convolution and self-attention are two powerful techniques for represent...
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09/03/2021
Towards Learning Spatially Discriminative Feature Representations
The backbone of traditional CNN classifier is generally considered as a ...
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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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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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12/21/2020
3D Object Detection with Pointformer
Feature learning for 3D object detection from point clouds is very chall...
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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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03/16/2020
Resolution Adaptive Networks for Efficient Inference
Recently, adaptive inference is gaining increasing attention due to its ...
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03/16/2020
Self-Supervised Discovering of Causal Features: Towards Interpretable Reinforcement Learning
Deep reinforcement learning (RL) has recently led to many breakthroughs ...
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03/06/2020
Smart Train Operation Algorithms based on Expert Knowledge and Reinforcement Learning
During recent decades, the automatic train operation (ATO) system has be...
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11/27/2019
A selected review on reinforcement learning based control for autonomous underwater vehicles
Recently, reinforcement learning (RL) has been extensively studied and a...
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09/26/2019
Implicit Semantic Data Augmentation for Deep Networks
In this paper, we propose a novel implicit semantic data augmentation (I...
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09/07/2019
Regularized Anderson Acceleration for Off-Policy Deep Reinforcement Learning
Model-free deep reinforcement learning (RL) algorithms have been widely ...
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09/07/2019
Multi Pseudo Q-learning Based Deterministic Policy Gradient for Tracking Control of Autonomous Underwater Vehicles
This paper investigates trajectory tracking problem for a class of under...
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09/07/2019
Soft Policy Gradient Method for Maximum Entropy Deep Reinforcement Learning
Maximum entropy deep reinforcement learning (RL) methods have been demon...
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12/11/2018