mPLUG-Owl & mPLUG-Owl2: Modularized Multimodal Large Language Model
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Updated
Apr 5, 2024 - Python
mPLUG-Owl & mPLUG-Owl2: Modularized Multimodal Large Language Model
[ICLR 2024] Official PyTorch implementation of FasterViT: Fast Vision Transformers with Hierarchical Attention
Official PyTorch implementation of Fully Attentional Networks
[ICML 2023] Official PyTorch implementation of Global Context Vision Transformers
Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)
GPT4Vis: What Can GPT-4 Do for Zero-shot Visual Recognition?
Multimodal Prompting with Missing Modalities for Visual Recognition, CVPR'23
Deep Isometric Learning for Visual Recognition (ICML 2020)
Improving Generalization via Scalable Neighborhood Component Analysis
PyTorch reimplementation of the paper "Involution: Inverting the Inherence of Convolution for Visual Recognition" (2D and 3D Involution) [CVPR 2021].
[ICLR 2023 Spotlight] GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation
Deep Understanding of Traffic Scenes for Autonomous Driving
This repository contains the ViewFool and ImageNet-V proposed by the paper “ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints” (NeurIPS2022).
[TMLR] "Adversarial Feature Augmentation and Normalization for Visual Recognition", Tianlong Chen, Yu Cheng, Zhe Gan, Jianfeng Wang, Lijuan Wang, Zhangyang Wang, Jingjing Liu
Implementation for <Orthogonal Over-Parameterized Training> in CVPR'21.
[ICCV W] Contextual Convolutional Neural Networks (https://arxiv.org/pdf/2108.07387.pdf)
Un proyecto open source de visión artificial para reconocer la portada de libros implementado en TensorFlow.
Code for "Learning a smooth kernel regularizer for convolutional neural networks" (Feinman & Lake, 2019)
Build Change - Post-Disaster Rapid Response Retrofit. Following Build Change's main premise to Build Disaster Resistant Buildings and Change Construction Practices Permanently, PD3R Team's main objective is to improve the safety conditions of buildings and reduce human and economic loss after the occurrence of a natural disaster.
IBM Watson's Visual Recognition
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