https://github.com/BunsenFeng/M-AbstainQA
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants
Papers with Code 아카이브
Visual Question Answering (VQA)
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Visual Question Answering (VQA) is a task in computer vision that involves answering questions about an image. The goal of VQA is to teach machines to understand the content of an image and answer questions about it in natural language.
Image Source: visualqa.org
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/CMU-CREATE-Lab/deep-smoke-machine
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/CPJKU/audio_conditioned_unet
https://github.com/CVxTz/ECG_Heartbeat_Classification
ECG Heartbeat Classification: A Deep Transferable Representation
https://github.com/Chaolei98/FreeZAD
CoCa: Contrastive Captioners are Image-Text Foundation Models
https://github.com/ChestnutLi/tf-faster-rcnn
https://github.com/China-UK-ZSL/Resources_for_KZSL
https://github.com/Cloud-CV/Grad-CAM
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/Cloud-CV/vilbert-multi-task
12-in-1: Multi-Task Vision and Language Representation Learning
https://github.com/Cloud-CV/visual-chatbot
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/Cremiy/visdial-rl
Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning
https://github.com/Cyanogenoid/pytorch-vqa
Show, Ask, Attend, and Answer: A Strong Baseline For Visual Question Answering
https://github.com/DS4SD/MarkushGrapher
Unifying Vision, Text, and Layout for Universal Document Processing
https://github.com/Deepak3994/Grad-Cam
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/Deepak3994/grad-cam-editted
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/Divs1159/STING-BEE
STING-BEE: Towards Vision-Language Model for Real-World X-ray Baggage Security Inspection
https://github.com/Dlut-lab-zmn/Image-Captioning-Attack
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/DongjunLee/dmn-tensorflow
Dynamic Memory Networks for Visual and Textual Question Answering
https://github.com/Drajan/DDxNet
ECG Heartbeat Classification: A Deep Transferable Representation
https://github.com/Eljefemasao/Customed-Object-Detector
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/Eljefemasao/MarkNet-ObjectDetector
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/FJSam/SelfCritical_ImageCaptioning
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/Fangyin1994/KCL
https://github.com/FengSuSky/CCB-VQA
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/FerryHuang/SimVLM
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision
https://github.com/Fragjacker/Pointcloud-grad-CAM
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/FrancescoSaverioZuppichini/A-journey-into-Convolutional-Neural-Network-visualization-
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/FudanNLP/UNet
U-Net: Machine Reading Comprehension with Unanswerable Questions
https://github.com/FuxiaoLiu/VisualNews-Repository
Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
https://github.com/Glaciohound/VCML
https://github.com/GuessWhatGame/clevr
https://github.com/GuessWhatGame/guesswhat
GuessWhat?! Visual object discovery through multi-modal dialogue
https://github.com/Gunnika/Visual-Question-Answering
Show, Ask, Attend, and Answer: A Strong Baseline For Visual Question Answering
https://github.com/H-Freax/ThinkGrasp
https://github.com/HKUST-KnowComp/MnemonicReader
Reinforced Mnemonic Reader for Machine Reading Comprehension
https://github.com/Hydragon516/Grad-CAM-pytorch
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.