CharlesNeilWilliams / TMELinks
[CVPR 2025] Official Pytorch implementation of "Learning with Noisy Triplet Correspondence for Composed Image Retrieval".
☆19Updated 5 months ago
Alternatives and similar repositories for TME
Users that are interested in TME are comparing it to the libraries listed below
Sorting:
- PyTorch implementation for Cross-modal Retrieval with Noisy Correspondence via Consistency Refining and Mining (TIP 2024)☆17Updated last year
- This is a summary of research on noisy correspondence. There may be omissions. If anything is missing please get in touch with us. Our em…☆105Updated this week
- This is a summary of research on noisy correspondence. There may be omissions. If anything is missing please get in touch with us. Our em…☆74Updated 3 weeks ago
- The official implementation of paper "Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval" accepted by NeurIPS…☆27Updated last year
- [SIGIR 2024] - Simple but Effective Raw-Data Level Multimodal Fusion for Composed Image Retrieval☆43Updated last year
- Codes of the Fine-grained Textual Inversion network for Zero-Shot Composed Image Retrieval☆26Updated 7 months ago
- 【ICLR 2024, Spotlight】Sentence-level Prompts Benefit Composed Image Retrieval☆91Updated last year
- Deep Evidential Learning with Noisy Correspondence for Cross-modal Retrieval ( ACM Multimedia 2022, Pytorch Code)☆47Updated last year
- Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models (AAAI 2024)☆73Updated 9 months ago
- The code of the paper "Negative Pre-aware for Noisy Cross-modal Matching" in AAAI 2024.☆25Updated 4 months ago
- Context-I2W: Mapping Images to Context-dependent words for Accurate Zero-Shot Composed Image Retrieval [AAAI 2024 Oral]☆55Updated 6 months ago
- ☆16Updated 2 years ago
- ☆78Updated 2 years ago
- Cross-modal Active Complementary Learning with Self-refining Correspondence (NeurIPS 2023, Pytorch Code)☆16Updated last year
- ☆29Updated last year
- ☆27Updated 2 years ago
- Source code of our AAAI 2024 paper "Cross-Modal and Uni-Modal Soft-Label Alignment for Image-Text Retrieval"☆50Updated last year
- ☆12Updated last year
- ☆11Updated last year
- Adaptation of vision-language models (CLIP) to downstream tasks using local and global prompts.☆49Updated 4 months ago
- Uncertainty-Guided Noisy Correspondence Learning for Efficient Cross-Modal Matching (ACM SIGIR 2024, Pytorch Code)☆24Updated 9 months ago
- [ICML 2024] "Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models"☆57Updated last year
- A comprehensive survey of Composed Multi-modal Retrieval (CMR), including Composed Image Retrieval (CIR) and Composed Video Retrieval (CV…☆69Updated 3 months ago
- Code and Dataset for the paper "LAMM: Label Alignment for Multi-Modal Prompt Learning" AAAI 2024☆33Updated last year
- USER: Unified Semantic Enhancement with Momentum Contrast for Image-Text Retrieval, TIP 2024☆33Updated 5 months ago
- [ACM MM 2024] Pytorch Code for the paper "Robust Variational Contrastive Learning for Partially View-unaligned Clustering"☆13Updated 10 months ago
- [ICML2024] Official PyTorch implementation of CoMC: Language-Driven Cross-Modal Classifier for Zero-Shot Multi-Label Image Recognition☆16Updated last year
- Pytorch implementation of "Test-time Adaption against Multi-modal Reliability Bias".☆44Updated 11 months ago
- [TIP2023] The code of “Plug-and-Play Regulators for Image-Text Matching”☆33Updated last year
- ☆36Updated last year