https://github.com/dcdcvgroup/vglaw-mindspore
공식 코드Language Adaptive Weight Generation for Multi-task Visual Grounding
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/dmmm1997/c3vg
공식 코드Multi-task Visual Grounding with Coarse-to-Fine Consistency Constraints
https://github.com/fightingfighting/ck-transformer
공식 코드CK-Transformer: Commonsense Knowledge Enhanced Transformers for Referring Expression Comprehension
https://github.com/gingl/earn
공식 코드Entity-enhanced Adaptive Reconstruction Network for Weakly Supervised Referring Expression Grounding
https://github.com/gtziafas/hots
공식 코드Enhancing Interpretability and Interactivity in Robot Manipulation: A Neurosymbolic Approach
https://github.com/guanrunwei/talk2radar
공식 코드Talk2Radar: Bridging Natural Language with 4D mmWave Radar for 3D Referring Expression Comprehension
https://github.com/hazananayurt/viref
공식 코드Searching for Ambiguous Objects in Videos using Relational Referring Expressions
https://github.com/henghuiding/ReLA
공식 코드https://github.com/henghuiding/grefcoco
공식 코드https://github.com/heshuting555/dshmp
공식 코드Decoupling Static and Hierarchical Motion Perception for Referring Video Segmentation
https://github.com/hit-sirs/crobim
공식 코드Cross-Modal Bidirectional Interaction Model for Referring Remote Sensing Image Segmentation
https://github.com/hon-wong/elysium
공식 코드Elysium: Exploring Object-level Perception in Videos via MLLM
https://github.com/hustvl/evf-sam
공식 코드EVF-SAM: Early Vision-Language Fusion for Text-Prompted Segment Anything Model
https://github.com/hustvl/groundingsuite
공식 코드GroundingSuite: Measuring Complex Multi-Granular Pixel Grounding
https://github.com/idea-research/groundingdino
공식 코드Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
https://github.com/ilkerkesen/bvpr
공식 코드Modulating Bottom-Up and Top-Down Visual Processing via Language-Conditional Filters
https://github.com/insomnia94/DTWREG
공식 코드Discriminative Triad Matching and Reconstruction for Weakly Referring Expression Grounding
https://github.com/insomnia94/ISREG
공식 코드Iterative Shrinking for Referring Expression Grounding Using Deep Reinforcement Learning
https://github.com/j-min/VL-T5
공식 코드https://github.com/jackroos/VL-BERT
공식 코드VL-BERT: Pre-training of Generic Visual-Linguistic Representations
https://github.com/jacobandreas/pragma
공식 코드Reasoning About Pragmatics with Neural Listeners and Speakers
https://github.com/jamespark3922/localized-skd
공식 코드Localized Symbolic Knowledge Distillation for Visual Commonsense Models
https://github.com/jamespark3922/lskd
공식 코드Localized Symbolic Knowledge Distillation for Visual Commonsense Models
https://github.com/jchiyah/what-are-you-referring-to
공식 코드https://github.com/jefferyzhan/griffon
공식 코드Griffon: Spelling out All Object Locations at Any Granularity with Large Language Models
https://github.com/jierunchen/ref-l4
공식 코드Revisiting Referring Expression Comprehension Evaluation in the Era of Large Multimodal Models
https://github.com/jinyuanli0012/pgim
공식 코드LLMs as Bridges: Reformulating Grounded Multimodal Named Entity Recognition
https://github.com/jwh97nn/anyref
공식 코드Multi-modal Instruction Tuned LLMs with Fine-grained Visual Perception
https://github.com/kpeng9510/ravar
공식 코드https://github.com/lancasterli/refsam
공식 코드RefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object Segmentation
https://github.com/leaplabthu/gsva
공식 코드GSVA: Generalized Segmentation via Multimodal Large Language Models
https://github.com/leon1207/3dreftr
공식 코드https://github.com/leotam/MIMIC-CXR-annotations
공식 코드https://github.com/lichengunc/MAttNet
공식 코드MAttNet: Modular Attention Network for Referring Expression Comprehension
https://github.com/lichengunc/refer
공식 코드https://github.com/liujunzhuo/FineCops-Ref
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.