Vision CAIR Research Group在GitHub上的公开存在展示了其在人工智能和计算机视觉领域的贡献。该组织的主要编程语言包括Python和Jupyter Notebook，开发了一系列知名项目，如MiniGPT-4和ChatCaptioner，涵盖了从视频理解到情感图像字幕生成的广泛应用。
顶级语言
公共仓库
MiniGPT-4
Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)
MiniGPT4-video
Official code for Goldfish model for long video understanding and MiniGPT4-video for short video understanding
ChatCaptioner
Official Repository of ChatCaptioner
LongVU
[ICML 2025] Official PyTorch implementation of LongVU
VisualGPT
VisualGPT, CVPR 2022 Proceeding, GPT as a decoder for vision-language models
MiniGPT-Med
Open-sourced code of MiniGPT-Med
3DCoMPaT-v2
3DCoMPaT++: An improved large-scale 3D vision dataset for compositional recognition
MammalNet
此仓库未提供描述。
LTVRR
此仓库未提供描述。
artemis-v2
Code for the paper: It is Okay to Not Be Okay: Overcoming Emotional Bias in Affective Image Captioning by Contrastive Data Collection
RelTransformer
此仓库未提供描述。
dochaystacks
Document Haystacks: Vision-Language Reasoning Over Piles of 1000+ Documents, CVPR 2025
Infinibench
Official InfiniBench: A Benchmark for Large Multi-Modal Models in Long-Form Movies and TV Shows
3DCoMPaT
Official repository for the 3DCoMPaT dataset (ECCV2022 Oral)
iMotion-LLM
此仓库未提供描述。
affectiveVisDial
此仓库未提供描述。
saai-factory-tutorial-creative-ai
Creative AI for Visual Art and Music slides and demos.
AF-Guide
Official repository of Action-Free Guide
CWAN
Creative Walk Adversarial Networks: Novel Art Generation with Probabilistic Random Walk Deviation from Style Norms
Freshness-Aware-PER
此仓库未提供描述。
HalentNet
此仓库未提供描述。
CIZSLv2
CIZSL++: Creativity Inspired Generative Zero-Shot Learning. T-PAMI under review.
WAGA
Code for Wölfflin Affective Generative Analysis paper published in ICCC 2021
cs326-few-shot-classification
CS326 Practical assignment #2: few-shot classification
GRaWD
Imaginative Walks: Generative Random Walk Deviation Loss for Improved Unseen Learning Representation. CVPR 2022 Workshop, ICCC 2022.
artelingo
此仓库未提供描述。
UnlikelihoodMotionForecasting
此仓库未提供描述。
HomeGPT
此仓库未提供描述。
ROLL
An Efficient and User-Friendly Scaling Library for Reinforcement Learning with Large Language Models
Goldfish_website
此仓库未提供描述。
3dreftransformer
此仓库未提供描述。
FishNet2.0
此仓库未提供描述。
affective-vision-language
此仓库未提供描述。
Zero-Shot-Learning
VisionCAIR Zero-Shot Learning Research
Affective-and-Creative-AI
VisionCAIR Affective and Creative AI Research
lifelong_fact_learning
此仓库未提供描述。
feelings
此仓库未提供描述。
CIZSL
Creativity Inspired Zero-Shot Learning
GDPP
Generator loss to reduce mode-collapse and to improve the generated samples quality.
常见问题
Vision-CAIR在GitHub上构建了什么？
Vision-CAIR主要开发与人工智能和计算机视觉相关的项目，包括MiniGPT-4和ChatCaptioner等，致力于推动相关技术的开源共享与应用。
Vision-CAIR使用哪些编程语言？
Vision-CAIR的主要编程语言包括Python和Jupyter Notebook，此外还使用HTML和JavaScript。这些语言的组合使其能够开发多功能的机器学习和数据科学项目。
Vision-CAIR的代码库是公开的吗？
是的，Vision-CAIR的所有代码库都是公开的，允许开发者和研究人员访问其开源项目，促进合作和技术传播。