https://github.com/Rishit-dagli/Visualize.AI
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Papers with Code 아카이브
Visual Question Answering (VQA)
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/RohanSaxena14/mrc-for-flat-nested-ner-in-tensoflow
https://github.com/RookieZB/duma_implementation_by_tf2
https://github.com/RuizhiZhang/MManGoCam
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/RuoyuChen10/objectdetection-saliency-maps
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/RylanSchaeffer/prismatic-vlms
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models
https://github.com/SDLZY/VCR_Align
https://github.com/SDaydreamer/VisualQA_Project
https://github.com/SJTU-VLG/ImageCaption-LBPF-qy
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/SatyamGaba/visual_question_answering
https://github.com/SatyamGaba/vqa
https://github.com/Sejong-VLI/VQA-LRCE-KBS-2023
https://github.com/SelinaFelton/SMA
https://github.com/SeolhwaLee/ParlAI_blender_persona
https://github.com/ShahinSHH/COVID-FACT
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/ShannonAI/Entity-Relation-As-Multi-Turn-QA
https://github.com/ShaojieJiang/FACE_orig
https://github.com/ShaojieJiang/tldr
https://github.com/Shivanshu-Gupta/Visual-Question-Answering
https://github.com/Shivmohith/Visual-Assistance-for-the-Blind
https://github.com/Shubhambindal2017/Unoffical-Implementation-of-GRAD-CAM-with-Sanity-Checks
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/SkyOL5/VQA-CoAttention
https://github.com/Sooram/GradCam-tensorflow
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/Sreyan88/GAMA
https://github.com/Stephenfang51/Grad_CAM
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/Stomper10/CheXpert
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/SuchismitaSahu1993/VQA-System
https://github.com/Swati17293/HQS
Hierarchical Deep Multi-modal Network for Medical Visual Question Answering
https://github.com/Tashnim-Chowdhury/FloodNet-Challenge-EARTHVISION2021
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
https://github.com/ThanThoai/Visual-Question-Answering_Vietnamese
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/TheInfamousWayne/CheXNet
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/TingAnChien/san-vqa-tensorflow
https://github.com/TooTouch/WhiteBox-Part1
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/TsingZ0/GFL
Think Locally, Act Globally: Federated Learning with Local and Global Representations
https://github.com/TsingZ0/PFL-Non-IID
Think Locally, Act Globally: Federated Learning with Local and Global Representations
https://github.com/UCSB-VRL/GTNet
VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.