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07/27/2023
Text-guided Foundation Model Adaptation for Pathological Image Classification
The recent surge of foundation models in computer vision and natural lan...
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03/12/2023
Towards General Purpose Medical AI: Continual Learning Medical Foundation Model
Inevitable domain and task discrepancies in real-world scenarios can imp...
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10/25/2022
MAROAM: Map-based Radar SLAM through Two-step Feature Selection
In this letter, we propose MAROAM, a millimeter wave radar-based SLAM fr...
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09/19/2022
Decentralized Vehicle Coordination: The Berkeley DeepDrive Drone Dataset
Decentralized multiagent planning has been an important field of researc...
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07/07/2022
Back to the Source: Diffusion-Driven Test-Time Adaptation
Test-time adaptation harnesses test inputs to improve the accuracy of a ...
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06/22/2022
GACT: Activation Compressed Training for General Architectures
Training large neural network (NN) models requires extensive memory reso...
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04/21/2022
Contrastive Test-Time Adaptation
Test-time adaptation is a special setting of unsupervised domain adaptat...
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09/02/2021
On-target Adaptation
Domain adaptation seeks to mitigate the shift between training on the so...
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05/18/2021
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks
Adversarial attacks optimize against models to defeat defenses. Existing...
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04/29/2021
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
The increasing size of neural network models has been critical for impro...
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06/19/2020
BEV-Seg: Bird's Eye View Semantic Segmentation Using Geometry and Semantic Point Cloud
Bird's-eye-view (BEV) is a powerful and widely adopted representation fo...
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06/18/2020
Fully Test-time Adaptation by Entropy Minimization
Faced with new and different data during testing, a model must adapt its...
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06/12/2020
CoDeNet: Algorithm-hardware Co-design for Deformable Convolution
Deploying deep learning models on embedded systems for computer vision t...
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02/19/2020
Algorithm-hardware Co-design for Deformable Convolution
FPGAs provide a flexible and efficient platform to accelerate rapidly-ch...
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08/08/2019
Dynamic Scale Inference by Entropy Minimization
Given the variety of the visual world there is not one true scale for re...
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05/16/2019
Monocular Plan View Networks for Autonomous Driving
Convolutions on monocular dash cam videos capture spatial invariances in...
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04/25/2019
Blurring the Line Between Structure and Learning to Optimize and Adapt Receptive Fields
The visual world is vast and varied, but its variations divide into stru...
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04/16/2019
Objects as Points
Detection identifies objects as axis-aligned boxes in an image. Most suc...
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01/07/2019
Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation
Convolutional Neural Networks (CNN) have been successful in processing d...
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11/26/2018
Joint Monocular 3D Vehicle Detection and Tracking
3D vehicle detection and tracking from a monocular camera requires detec...
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11/13/2018
Deep Object Centric Policies for Autonomous Driving
While learning visuomotor skills in an end-to-end manner is appealing, d...
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10/18/2017
VisDA: The Visual Domain Adaptation Challenge
We present the 2017 Visual Domain Adaptation (VisDA) dataset and challen...
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07/20/2017
Deep Layer Aggregation
Convolutional networks have had great success in image classification an...
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03/29/2017
Iterative Object and Part Transfer for Fine-Grained Recognition
The aim of fine-grained recognition is to identify sub-ordinate categori...
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12/08/2016
FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation
Fully convolutional models for dense prediction have proven successful f...
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12/08/2015
