yipoh

AesBench

An expert benchmark aiming to comprehensively evaluate the aesthetic perception capacities of MLLMs.

AesExpert

[ACMMM 2024] AesExpert: Towards Multi-modality Foundation Model for Image Aesthetics Perception

TAVAR

[TCSVT] Theme-aware Visual Attribute Reasoning for Image Aesthetics Assessment

SARQUE

[TMM] Explainable and Generalizable Blind Image Quality Assessment via Semantic Attribute Reasoning

DSS

[SPL] Blind Quality Index of Depth Images Based on Structural Statistics for View Synthesis

Awesome_Multimodel_LLM

Awesome_Multimodel is a curated GitHub repository that provides a comprehensive collection of resources for Multimodal Large Language Models (MLLM). It covers datasets, tuning techniques, in-context learning, visual reasoning, foundational models, and more. Stay updated with the latest advancement.

CODIF

[TCSVT] Predicting the Quality of View Synthesis With Color-Depth Image Fusion

aes-expert

AesNet

Multimodality Multi-attribute Contrastive Pre-training for Image Aesthetics Computing

Awesome-Aesthetic-Evaluation-and-Cropping

IQA-PyTorch

👁️ 🖼️ 🔥PyTorch Toolbox for Image Quality Assessment, including LPIPS, FID, NIQE, NRQM(Ma), MUSIQ, NIMA, DBCNN, WaDIQaM, BRISQUE, PI and more...

SIND

VLMEvalKit

Open-source evaluation toolkit of large vision-language models (LVLMs), support GPT-4v, Gemini, QwenVLPlus, 50+ HF models, 20+ benchmarks

yipoh

Config files for my GitHub profile.

yipoh.github.io