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06/30/2023
Towards Brain Inspired Design for Addressing the Shortcomings of ANNs
As our understanding of the mechanisms of brain function is enhanced, th...
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05/15/2023
Enhancing Performance of Vision Transformers on Small Datasets through Local Inductive Bias Incorporation
Vision transformers (ViTs) achieve remarkable performance on large datas...
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05/08/2023
BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning
The ability of deep neural networks to continually learn and adapt to a ...
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04/30/2023
Multi-Task Structural Learning using Local Task Similarity induced Neuron Creation and Removal
Multi-task learning has the potential to improve generalization by maxim...
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04/13/2023
LSFSL: Leveraging Shape Information in Few-shot Learning
Few-shot learning (FSL) techniques seek to learn the underlying patterns...
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04/13/2023
A Study of Biologically Plausible Neural Network: The Role and Interactions of Brain-Inspired Mechanisms in Continual Learning
Humans excel at continually acquiring, consolidating, and retaining info...
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03/18/2023
Learn, Unlearn and Relearn: An Online Learning Paradigm for Deep Neural Networks
Deep neural networks (DNNs) are often trained on the premise that the co...
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01/02/2023
Dynamically Modular and Sparse General Continual Learning
Real-world applications often require learning continuously from a strea...
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12/28/2022
Sparse Coding in a Dual Memory System for Lifelong Learning
Efficient continual learning in humans is enabled by a rich set of neuro...
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10/07/2022
AI-Driven Road Maintenance Inspection v2: Reducing Data Dependency Quantifying Road Damage
Road infrastructure maintenance inspection is typically a labor-intensiv...
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10/05/2022
Image Masking for Robust Self-Supervised Monocular Depth Estimation
Self-supervised monocular depth estimation is a salient task for 3D scen...
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08/23/2022
A Comprehensive Study of Real-Time Object Detection Networks Across Multiple Domains: A Survey
Deep neural network based object detectors are continuously evolving and...
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08/19/2022
Curbing Task Interference using Representation Similarity-Guided Multi-Task Feature Sharing
Multi-task learning of dense prediction tasks, by sharing both the encod...
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08/11/2022
Differencing based Self-supervised pretraining for Scene Change Detection
Scene change detection (SCD), a crucial perception task, identifies chan...
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07/14/2022
Adversarial Attacks on Monocular Pose Estimation
Advances in deep learning have resulted in steady progress in computer v...
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07/13/2022
Task Agnostic Representation Consolidation: a Self-supervised based Continual Learning Approach
Continual learning (CL) over non-stationary data streams remains one of ...
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07/11/2022
Consistency is the key to further mitigating catastrophic forgetting in continual learning
Deep neural networks struggle to continually learn multiple sequential t...
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06/12/2022
InBiaseD: Inductive Bias Distillation to Improve Generalization and Robustness through Shape-awareness
Humans rely less on spurious correlations and trivial cues, such as text...
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06/08/2022
SYNERgy between SYNaptic consolidation and Experience Replay for general continual learning
Continual learning (CL) in the brain is facilitated by a complex set of ...
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02/07/2022
Transformers in Self-Supervised Monocular Depth Estimation with Unknown Camera Intrinsics
The advent of autonomous driving and advanced driver assistance systems ...
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01/29/2022
Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System
Humans excel at continually learning from an ever-changing environment w...
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01/21/2022
A Comprehensive Study of Vision Transformers on Dense Prediction Tasks
Convolutional Neural Networks (CNNs), architectures consisting of convol...
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11/09/2021
Does Thermal data make the detection systems more reliable?
Deep learning-based detection networks have made remarkable progress in ...
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08/10/2021
UniNet: A Unified Scene Understanding Network and Exploring Multi-Task Relationships through the Lens of Adversarial Attacks
Scene understanding is crucial for autonomous systems which intend to op...
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06/30/2021
Improving the Efficiency of Transformers for Resource-Constrained Devices
Transformers provide promising accuracy and have become popular and used...
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06/06/2021
Highlighting the Importance of Reducing Research Bias and Carbon Emissions in CNNs
Convolutional neural networks (CNNs) have become commonplace in addressi...
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06/04/2021
AI Driven Road Maintenance Inspection
Road infrastructure maintenance inspection is typically a labour-intensi...
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05/06/2021
Challenges and Obstacles Towards Deploying Deep Learning Models on Mobile Devices
From computer vision and speech recognition to forecasting trajectories ...
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04/20/2021
Perceptual Loss for Robust Unsupervised Homography Estimation
Homography estimation is often an indispensable step in many computer vi...
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04/20/2021
Distill on the Go: Online knowledge distillation in self-supervised learning
Self-supervised learning solves pretext prediction tasks that do not req...
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03/03/2021
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation
Dense depth estimation is essential to scene-understanding for autonomou...
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12/15/2020
Practical Auto-Calibration for Spatial Scene-Understanding from Crowdsourced Dashcamera Videos
Spatial scene-understanding, including dense depth and ego-motion estima...
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09/17/2020
Noisy Concurrent Training for Efficient Learning under Label Noise
Deep neural networks (DNNs) fail to learn effectively under label noise ...
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08/16/2020
Adversarial Concurrent Training: Optimizing Robustness and Accuracy Trade-off of Deep Neural Networks
Adversarial training has been proven to be an effective technique for im...
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07/25/2020
Crowdsourced 3D Mapping: A Combined Multi-View Geometry and Self-Supervised Learning Approach
The ability to efficiently utilize crowdsourced visual data carries imme...
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07/09/2020
Monocular Vision based Crowdsourced 3D Traffic Sign Positioning with Unknown Camera Intrinsics and Distortion Coefficients
Autonomous vehicles and driver assistance systems utilize maps of 3D sem...
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07/03/2020
Knowledge Distillation Beyond Model Compression
Knowledge distillation (KD) is commonly deemed as an effective model com...
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12/03/2019
RGPNet: A Real-Time General Purpose Semantic Segmentation
We propose a novel real-time general purpose semantic segmentation archi...
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10/11/2019
