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09/07/2023
ImageBind-LLM: Multi-modality Instruction Tuning
We present ImageBind-LLM, a multi-modality instruction tuning method of ...
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07/28/2023
Beating Backdoor Attack at Its Own Game
Deep neural networks (DNNs) are vulnerable to backdoor attack, which doe...
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07/20/2023
Meta-Transformer: A Unified Framework for Multimodal Learning
Multimodal learning aims to build models that can process and relate inf...
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07/06/2023
3D Environment Modeling for Falsification and Beyond with Scenic 3.0
We present a major new version of Scenic, a probabilistic programming la...
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04/28/2023
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
How to efficiently transform large language models (LLMs) into instructi...
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03/12/2023
Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models
Continual learning (CL) can help pre-trained vision-language models effi...
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08/18/2022
Prompt Vision Transformer for Domain Generalization
Though vision transformers (ViTs) have exhibited impressive ability for ...
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10/27/2021
2nd Place Solution for VisDA 2021 Challenge – Universally Domain Adaptive Image Recognition
The Visual Domain Adaptation (VisDA) 2021 Challenge calls for unsupervis...
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09/25/2021
Multi-source Few-shot Domain Adaptation
Multi-source Domain Adaptation (MDA) aims to transfer predictive models ...
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09/14/2021
Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data
Background: At the onset of a pandemic, such as COVID-19, data with prop...
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07/03/2021
Scene-aware Learning Network for Radar Object Detection
Object detection is essential to safe autonomous or assisted driving. Pr...
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06/08/2021
Image2Point: 3D Point-Cloud Understanding with Pretrained 2D ConvNets
3D point-clouds and 2D images are different visual representations of th...
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03/23/2021
Self-Supervised Pretraining Improves Self-Supervised Pretraining
While self-supervised pretraining has proven beneficial for many compute...
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11/30/2020
A Customizable Dynamic Scenario Modeling and Data Generation Platform for Autonomous Driving
Safely interacting with humans is a significant challenge for autonomous...
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11/25/2020
Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation
Thanks to large-scale labeled training data, deep neural networks (DNNs)...
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11/17/2020
Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources
Sentiment analysis of user-generated reviews or comments on products and...
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10/13/2020
Scenic: A Language for Scenario Specification and Data Generation
We propose a new probabilistic programming language for the design and a...
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10/02/2020
Pre-Training by Completing Point Clouds
There has recently been a flurry of exciting advances in deep learning m...
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09/01/2020
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation
Large-scale labeled training datasets have enabled deep neural networks ...
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08/20/2020
Generalizing Fault Detection Against Domain Shifts Using Stratification-Aware Cross-Validation
Incipient anomalies present milder symptoms compared to severe ones, and...
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08/20/2020
Using Ensemble Classifiers to Detect Incipient Anomalies
Incipient anomalies present milder symptoms compared to severe ones, and...
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07/12/2020
Exploiting Uncertainties from Ensemble Learners to Improve Decision-Making in Healthcare AI
Ensemble learning is widely applied in Machine Learning (ML) to improve ...
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03/31/2020
PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation
The requirement of fine-grained perception by autonomous driving systems...
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10/27/2019
Multi-source Domain Adaptation for Semantic Segmentation
Simulation-to-real domain adaptation for semantic segmentation has been ...
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09/02/2019
Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization without Accessing Target Domain Data
We propose to harness the potential of simulation for the semantic segme...
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11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
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10/11/2018
A Novel Domain Adaptation Framework for Medical Image Segmentation
We propose a segmentation framework that uses deep neural networks and i...
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09/25/2018
Scenic: Language-Based Scene Generation
Synthetic data has proved increasingly useful in both training and testi...
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09/22/2018
SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud
Earlier work demonstrates the promise of deep-learning-based approaches ...
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05/17/2018
Counterexample-Guided Data Augmentation
We present a novel framework for augmenting data sets for machine learni...
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03/31/2018
A LiDAR Point Cloud Generator: from a Virtual World to Autonomous Driving
3D LiDAR scanners are playing an increasingly important role in autonomo...
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03/23/2018
SqueezeNext: Hardware-Aware Neural Network Design
One of the main barriers for deploying neural networks on embedded syste...
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11/22/2017
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions
Neural networks rely on convolutions to aggregate spatial information. H...
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10/19/2017