ByungKwanLee

Awesome-Multimodal-Large-Language-Models

:sparkles::sparkles:Latest Advances on Multimodal Large Language Models

Adversarial-Information-Bottleneck

[NeurIPS 2021] Official PyTorch Implementation for "Distilling Robust and Non-Robust Features in Adversarial Examples by Information Bottleneck"

Causal-Adversarial-Instruments

[CVPR 2023] Official PyTorch Implementation for "Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable Regression"

CoLLaVO

[ACL 2024 Findings] Official PyTorch Implementation code for realizing the technical part of CoLLaVO: Crayon Large Language and Vision mOdel to significantly improve zero-shot vision language performances

Full-Segment-Anything

This is Pytorch Implementation Code for adding new features in code of Segment-Anything. Here, the features support batch-input on the full-grid prompt (automatic mask generation) with post-processing: removing duplicated or small regions and holes, under flexible input image size

Meteor

[NeurIPS 2024] Official PyTorch implementation code for realizing the technical part of Mamba-based traversal of rationale (Meteor) to improve performance of numerous vision language performances for diverse capabilities.

MoAI

[ECCV 2024] Official PyTorch implementation code for realizing the technical part of Mixture of All Intelligence (MoAI) to improve performance of numerous zero-shot vision language tasks.

Phantom

[Under Review] Official PyTorch implementation code for realizing the technical part of Phantom of Latent representing equipped with enlarged hidden dimension to build super frontier vision language models.

Super-Fast-Adversarial-Training

Official PyTorch Implementation Code for Developing Super Fast Adversarial Training with Distributed Data Parallel, Channel Last Memory Format, Mixed Precision Training + Adversarial Attack, Faster Adversarial Training, and Fast Forward Computer Vision (FFCV).

TroL

[EMNLP 2024] Official PyTorch implementation code for realizing the technical part of Traversal of Layers (TroL) presenting new propagation operation to get super vision language performances.

ByungKwanLee/MoAI

[ECCV 2024] Official PyTorch implementation code for realizing the technical part of Mixture of All Intelligence (MoAI) to improve performance of numerous zero-shot vision language tasks.

ByungKwanLee/Full-Segment-Anything

This is Pytorch Implementation Code for adding new features in code of Segment-Anything. Here, the features support batch-input on the full-grid prompt (automatic mask generation) with post-processing: removing duplicated or small regions and holes, under flexible input image size

ByungKwanLee/Meteor

[NeurIPS 2024] Official PyTorch implementation code for realizing the technical part of Mamba-based traversal of rationale (Meteor) to improve performance of numerous vision language performances for diverse capabilities.

ByungKwanLee/CoLLaVO

[ACL 2024 Findings] Official PyTorch Implementation code for realizing the technical part of CoLLaVO: Crayon Large Language and Vision mOdel to significantly improve zero-shot vision language performances

ByungKwanLee/TroL

[EMNLP 2024] Official PyTorch implementation code for realizing the technical part of Traversal of Layers (TroL) presenting new propagation operation to get super vision language performances.

ByungKwanLee/Phantom

[Under Review] Official PyTorch implementation code for realizing the technical part of Phantom of Latent representing equipped with enlarged hidden dimension to build super frontier vision language models.

ByungKwanLee/Adversarial-Information-Bottleneck

[NeurIPS 2021] Official PyTorch Implementation for "Distilling Robust and Non-Robust Features in Adversarial Examples by Information Bottleneck"

ByungKwanLee/Causal-Adversarial-Instruments

[CVPR 2023] Official PyTorch Implementation for "Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable Regression"

ByungKwanLee/Super-Fast-Adversarial-Training

Official PyTorch Implementation Code for Developing Super Fast Adversarial Training with Distributed Data Parallel, Channel Last Memory Format, Mixed Precision Training + Adversarial Attack, Faster Adversarial Training, and Fast Forward Computer Vision (FFCV).

ByungKwanLee/Double-Debiased-Adversary

[ICCV 2023] Official PyTorch Implementation for "Mitigating Adversarial Vulnerability through Causal Parameter Estimation by Adversarial Double Machine Learning"

ByungKwanLee/Masking-Adversarial-Damage

[CVPR 2022] Official PyTorch Implementation for "Masking Adversarial Damage: Finding Adversarial Saliency for Robust and Sparse Network"

ByungKwanLee/Adavanced-ECMS

Advanced Energy Control Management System (Advanced-ECMS) for Electrical Vehicle System using proposed Plus Version of Alternating Direction Method of Multipliers (ADMM+) on Robotics Operating System (ROS)

ByungKwanLee/Robust-TopView

Robustly Converting Camera View from Normal View to Top View for Autonomous Vehicle System on Robotics Operating System (ROS)

ByungKwanLee/Hierarchical-Bayesian-Defense

[OpenReview] Official PyTorch Implementation for "Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical Variational Inference"

ByungKwanLee/YOLO-Dyanmic-ROS

Modification to YOLO for improving Dynamic Real-Time Processing on Robotics Operating Systems for Autonomous Vehicle System

ByungKwanLee/Causal-Unsupervised-Segmentation

Official PyTorch Implementation code for realizing the technical part of Causal Unsupervised Semantic sEgmentation (CAUSE) to improve performance of unsupervised semantic segmentation. (Under Review)

ByungKwanLee/ByungKwanLee

ByungKwanLee/VLsI-page