Papers with Code 아카이브
Cross-Modal Retrieval
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Cross-Modal Retrieval (CMR) is a task of retrieving items across different modalities, such as image, text, video, and audio. The core challenge of CMR is the heterogeneity gap, which arises because data from different modalities have distinct representations, making direct comparison difficult. To address this, most CMR methods focus on learning a shared latent embedding space. In this space, concepts from different modalities are projected, allowing their similarity to be measured using a distance metric.
Scene-centric vs. Object-centric Image-Text Cross-modal Retrieval: A Reproducibility Study
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ioanacroi/qb-norm
공식 코드https://github.com/ivana-13/guided_masking
공식 코드Beyond Image-Text Matching: Verb Understanding in Multimodal Transformers Using Guided Masking
https://github.com/jackroos/VL-BERT
공식 코드VL-BERT: Pre-training of Generic Visual-Linguistic Representations
https://github.com/jaeseokbyun/grit-vlp
공식 코드GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training
https://github.com/jeffhernandez1995/GenLlaVA
공식 코드https://github.com/jiangqy/DCMH-CVPR2017
공식 코드https://github.com/kaistmm/SSLalignment
공식 코드Aligning Sight and Sound: Advanced Sound Source Localization Through Audio-Visual Alignment
https://github.com/kdwonn/DivE
공식 코드Improving Cross-Modal Retrieval with Set of Diverse Embeddings
https://github.com/khdlr/SoundingEarth
공식 코드Self-supervised Audiovisual Representation Learning for Remote Sensing Data
https://github.com/kkzhang95/awesome-composed-multi-modal-retrieval
공식 코드Composed Multi-modal Retrieval: A Survey of Approaches and Applications
https://github.com/kuanghuei/SCAN
공식 코드https://github.com/kywen1119/DSRAN
공식 코드Learning Dual Semantic Relations with Graph Attention for Image-Text Matching
https://github.com/lancopku/IAIS
공식 코드Learning Relation Alignment for Calibrated Cross-modal Retrieval
https://github.com/layumi/Image-Text-Embedding
공식 코드Dual-Path Convolutional Image-Text Embeddings with Instance Loss
https://github.com/lelan-li/SSAH
공식 코드Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval
https://github.com/leolee99/pau
공식 코드Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval
https://github.com/letitiabanana/pnp-ovss
공식 코드Emergent Open-Vocabulary Semantic Segmentation from Off-the-shelf Vision-Language Models
https://github.com/lijiabei-7/leccr
공식 코드https://github.com/linzhiqiu/visual_gpt_score
공식 코드Revisiting the Role of Language Priors in Vision-Language Models
https://github.com/lionel-hing/bic-net
공식 코드BiC-Net: Learning Efficient Spatio-Temporal Relation for Text-Video Retrieval
https://github.com/lionel-hing/vsr-net
공식 코드BiC-Net: Learning Efficient Spatio-Temporal Relation for Text-Video Retrieval
https://github.com/littleredxh/vse-gradient
공식 코드Dissecting Deep Metric Learning Losses for Image-Text Retrieval
https://github.com/liuyyy111/d2s-vse
공식 코드https://github.com/llabres/library-dataset
공식 코드https://github.com/luminosityx/fne
공식 코드Your Negative May not Be True Negative: Boosting Image-Text Matching with False Negative Elimination
https://github.com/luminosityx/hat
공식 코드Unifying Two-Stream Encoders with Transformers for Cross-Modal Retrieval
https://github.com/luomancs/remuq
공식 코드https://github.com/lwaekfjlk/mmoe
공식 코드MMoE: Enhancing Multimodal Models with Mixtures of Multimodal Interaction Experts
https://github.com/m2man/LGSGM
공식 코드A Deep Local and Global Scene-Graph Matching for Image-Text Retrieval
https://github.com/magic-ai4med/kep
공식 코드Knowledge-enhanced Visual-Language Pretraining for Computational Pathology
https://github.com/mahmoodlab/titan
공식 코드https://github.com/mariyahendriksen/ecir23-object-centric-vs-scene-centric-cmr
공식 코드Scene-centric vs. Object-centric Image-Text Cross-modal Retrieval: A Reproducibility Study
https://github.com/mcgill-nlp/diffusion-itm
공식 코드https://github.com/mesnico/TERAN
공식 코드Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders
https://github.com/mesnico/TERN
공식 코드Transformer Reasoning Network for Image-Text Matching and Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.