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Phrase Grounding
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Given an image and a corresponding caption, the Phrase Grounding task aims to ground each entity mentioned by a noun phrase in the caption to a region in the image.
Source: Phrase Grounding by Soft-Label Chain Conditional Random Field
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BryanPlummer/cite
공식 코드https://github.com/BryanPlummer/phrase_detection
공식 코드Revisiting Image-Language Networks for Open-ended Phrase Detection
https://github.com/Claire1217/AGPT
공식 코드Anatomical grounding pre-training for medical phrase grounding
https://github.com/TheShadow29/zsgnet-pytorch
공식 코드Zero-Shot Grounding of Objects from Natural Language Queries
https://github.com/ZuyiZhou/Awesome-Interpretable-Cross-modal-Reasoning
공식 코드https://github.com/aarbelle/GroundingBySeparation
공식 코드https://github.com/akirafukui/vqa-mcb
공식 코드Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding
https://github.com/amzn/augment-the-pairs-wacv2024
공식 코드https://github.com/arminarj/empathic-grounding
공식 코드https://github.com/ashkamath/mdetr
공식 코드MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding
https://github.com/b-faye/lightmdetr
공식 코드A Lightweight Modular Framework for Low-Cost Open-Vocabulary Object Detection Training
https://github.com/bigai-research/vlgae
공식 코드https://github.com/bryanplummer/ssn
공식 코드https://github.com/eyalgomel/box-based-refinement
공식 코드Box-based Refinement for Weakly Supervised and Unsupervised Localization Tasks
https://github.com/hassanhub/MultiGrounding
공식 코드Multi-level Multimodal Common Semantic Space for Image-Phrase Grounding
https://github.com/idea-research/dq-detr
공식 코드DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding
https://github.com/izhx/phrase-grounding-with-pronoun
공식 코드Extending Phrase Grounding with Pronouns in Visual Dialogues
https://github.com/jacobswan1/MTG-pytorch
공식 코드https://github.com/jefferyzhan/griffon
공식 코드https://github.com/jhuang81/weak-sup-visual-grounding
공식 코드Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation
https://github.com/jnhwkim/ban-vqa
공식 코드https://github.com/lil-lab/phrase_grounding
공식 코드A Joint Study of Phrase Grounding and Task Performance in Vision and Language Models
https://github.com/liujch1998/SoftLabelCCRF
공식 코드Phrase Grounding by Soft-Label Chain Conditional Random Field
https://github.com/mbzuai-oryx/video-llava
공식 코드https://github.com/microsoft/GLIP
공식 코드https://github.com/microsoft/fiber
공식 코드Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone
https://github.com/microsoft/hi-ml/tree/main/hi-ml-multimodal
공식 코드Making the Most of Text Semantics to Improve Biomedical Vision--Language Processing
https://github.com/microsoft/unilm/tree/master/kosmos-2
공식 코드Kosmos-2: Grounding Multimodal Large Language Models to the World
https://github.com/mischad/chest-distillation
공식 코드Trade-offs in Fine-tuned Diffusion Models Between Accuracy and Interpretability
https://github.com/om-ai-lab/OmDet
공식 코드OmDet: Large-scale vision-language multi-dataset pre-training with multimodal detection network
https://github.com/open-mmlab/mmdetection
공식 코드An Open and Comprehensive Pipeline for Unified Object Grounding and Detection
https://github.com/pluslabnlp/envision
공식 코드Localizing Active Objects from Egocentric Vision with Symbolic World Knowledge
https://github.com/qinzzz/Multimodal-Alignment-Framework
공식 코드MAF: Multimodal Alignment Framework for Weakly-Supervised Phrase Grounding
https://github.com/rd20karim/synch-transformer
공식 코드Transformer with Controlled Attention for Synchronous Motion Captioning
https://github.com/sayeh1994/vicca
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.