https://github.com/liuting20/mapper
공식 코드MaPPER: Multimodal Prior-guided Parameter Efficient Tuning for Referring Expression Comprehension
Papers with Code 아카이브
Referring Expression
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Referring expressions places a bounding box around the instance corresponding to the provided description and image.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lluma/OCID-Ref
공식 코드OCID-Ref: A 3D Robotic Dataset with Embodied Language for Clutter Scene Grounding
https://github.com/luogen1996/MCN
공식 코드Multi-task Collaborative Network for Joint Referring Expression Comprehension and Segmentation
https://github.com/luogen1996/Real-time-Global-Inference-Network
공식 코드A Real-time Global Inference Network for One-stage Referring Expression Comprehension
https://github.com/luogen1996/laconvnet
공식 코드Towards Language-guided Visual Recognition via Dynamic Convolutions
https://github.com/luogen1996/simrec
공식 코드https://github.com/magic-research/Sa2VA
공식 코드https://github.com/mars-tin/pixrefer
공식 코드Vision-Language Models Are Not Pragmatically Competent in Referring Expression Generation
https://github.com/mbzuai-oryx/groundingLMM
공식 코드https://github.com/mc-lan/text4seg
공식 코드https://github.com/mcao610/ProfileREG
공식 코드https://github.com/mengcaopku/dcnet
공식 코드Correspondence Matters for Video Referring Expression Comprehension
https://github.com/microsoft/SoM
공식 코드Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V
https://github.com/microsoft/unilm/tree/master/kosmos-2
공식 코드Kosmos-2: Grounding Multimodal Large Language Models to the World
https://github.com/mikittt/Human-Friendly-REG
공식 코드Generating Easy-to-Understand Referring Expressions for Target Identifications
https://github.com/mikittt/easy-to-understand-REG
공식 코드Generating Easy-to-Understand Referring Expressions for Target Identifications
https://github.com/mjhucla/Google_Refexp_toolbox
공식 코드Generation and Comprehension of Unambiguous Object Descriptions
https://github.com/msiam/pixfoundation
공식 코드PixFoundation: Are We Heading in the Right Direction with Pixel-level Vision Foundation Models?
https://github.com/next-chatv/next-chat
공식 코드https://github.com/nineblu/omni-res
공식 코드https://github.com/nini0919/semires
공식 코드https://github.com/ofa-sys/ofa
공식 코드https://github.com/open-mmlab/mmdetection
공식 코드An Open and Comprehensive Pipeline for Unified Object Grounding and Detection
https://github.com/priya22/pdnc-lrec2022
공식 코드The Project Dialogism Novel Corpus: A Dataset for Quotation Attribution in Literary Texts
https://github.com/qzp2018/MCLN
공식 코드Multi-branch Collaborative Learning Network for 3D Visual Grounding
https://github.com/rd20karim/mb-ores
공식 코드MB-ORES: A Multi-Branch Object Reasoner for Visual Grounding in Remote Sensing
https://github.com/robertluo1/cohd
공식 코드https://github.com/rubics-xuan/mres
공식 코드Unveiling Parts Beyond Objects:Towards Finer-Granularity Referring Expression Segmentation
https://github.com/sean-zhuh/seqtr
공식 코드https://github.com/seonghoon-yu/zero-shot-ris
공식 코드Zero-shot Referring Image Segmentation with Global-Local Context Features
https://github.com/shikras/d-cube
공식 코드Described Object Detection: Liberating Object Detection with Flexible Expressions
https://github.com/show-han/zeroshot_rec
공식 코드Zero-shot Referring Expression Comprehension via Structural Similarity Between Images and Captions
https://github.com/shuheikurita/refego
공식 코드RefEgo: Referring Expression Comprehension Dataset from First-Person Perception of Ego4D
https://github.com/sibeiyang/sgmn
공식 코드Relationship-Embedded Representation Learning for Grounding Referring Expressions
https://github.com/sosppxo/3d-stmn
공식 코드https://github.com/sosppxo/MDIN
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.