Papers with Code 아카이브
Visual Question Answering
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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MLLM Leaderboard
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/homebrewltd/ichigo
https://github.com/hs2k/pytorch-smoothgrad
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/huan123/py-fatser-rcnn
https://github.com/huang-research-group/InstructionGPT-4
InstructionGPT-4: A 200-Instruction Paradigm for Fine-Tuning MiniGPT-4
https://github.com/hudaAlamri/DSTC7-Audio-Visual-Scene-Aware-Dialog-AVSD-Challenge
End-to-End Audio Visual Scene-Aware Dialog using Multimodal Attention-Based Video Features
https://github.com/huggingface/transformers
LXMERT: Learning Cross-Modality Encoder Representations from Transformers
https://github.com/huofushuo/SID
Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding
https://github.com/hwanheelee1993/vilbertscore
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
https://github.com/iammrhelo/pytorch-vqa-dan
Dual Attention Networks for Multimodal Reasoning and Matching
https://github.com/ibrahimSouleiman/GuessWhat
GuessWhat?! Visual object discovery through multi-modal dialogue
https://github.com/idiap/fullgrad-saliency
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/illume-unified-mllm/ILLUME_plus
ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and Diffusion Refinement
https://github.com/insigh/Faster-RCNN-Tensorflow
https://github.com/isaaccasm/GradCAM-keras
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/isaaccorley/resize-is-all-you-need
https://github.com/ismailuddin/gradcam-tensorflow-2
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/itanvir/gradcam
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/ithuanhuan/gpu-py3-faster-rcnn
https://github.com/ithuanhuan/py-fatser-rcnn
https://github.com/itsShnik/adaptively-finetuning-transformers
LXMERT: Learning Cross-Modality Encoder Representations from Transformers
https://github.com/jack-bo1220/awesome-remote-sensing-foundation-models
https://github.com/jackroos/pythia
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/jacobandreas/nmn2
https://github.com/jacobgil/keras-grad-cam
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/jacobgil/pytorch-grad-cam
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/jaehyunnn/RelationalNetwork_pytorch
https://github.com/jdai-cv/image-captioning
https://github.com/jiahuei/COMIC-Compact-Image-Captioning-with-Attention
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/jiahuei/COMIC-Towards-A-Compact-Image-Captioning-Model-with-Attention
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/jiahuei/Self-Critical-SCST-TensorFlow
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/jialinwu17/Self_Critical_VQA
Self-Critical Reasoning for Robust Visual Question Answering
https://github.com/jialinwu17/tmpimgs
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
https://github.com/jianjieluo/openai-clip-feature
https://github.com/jiasenlu/vilbert_beta
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
https://github.com/jiwanchung/vlis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.