Text based Person Retrieval ICFG-PEDES RDE mAP 40.06 # 4 Compare R@1 67.68 # 2 Compare R@5 82.47 # 1 Compare R@10 87.36 # 1 Compare mINP 7.87 # 2 Compare Text-based Person Retrieval with Noisy Correspondence RSTPReid RDE Rank 1 64.45 # 1 Compare Rank 10 90.00 #...
(3/13/2023) Code released! The goal of this work is to enhance global text-to-image person retrieval performance, without requiring any additional supervision and inference cost. To achieve this, we utilize the full CLIP model as our feature extraction backbone. Additionally, we propose a novel...
Person re-identificationDeep learningText-to-image person retrieval aims to retrieve relevant target individuals based on given textual descriptions. The main challenge faced by this task is how to better combine and align the features of both text and image modalities. Previous efforts have attempted...
@inproceedings{qin2022deep, title={Deep evidential learning with noisy correspondence for cross-modal retrieval}, author={Qin, Yang and Peng, Dezhong and Peng, Xi and Wang, Xu and Hu, Peng}, booktitle={Proceedings of the 30th ACM International Conference on Multimedia}, pages={4948--4956},...
The need for applying advanced social information retrieval techniques for personalizing web-based information discovery has been identified as a key challenge. Until now, significant R&D effort has been devoted aiming towards applying c... P Karampiperis,A Diplaros - Proc of the International Work...
Re-imagen: Retrieval-augmented text-to-image gen- erator. arXiv preprint arXiv:2209.14491, 2022. 6 [8] Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. BERT: Pre-training of deep bidirectional trans- formers for language understanding. In Proceedings of the 2019 Con...
ReCo also outperforms the real image retrieval baseline [45] and most prior studies [6, 10, 46, 50]. Limitations. Our method has several limitations. First, ReCo might generate lower-quality images when the in- put query becomes too challenging, e.g., the unusual giant "dog" in Figu...
This is to deal with the situation in which there are multiple people in the same image that we want to generate, so that the model knows which keypoint corresponds to which person. Each keypoint semantic embedding 𝒌e is a learnable vector; the dimension of each person token is set ...
High-fidelity Person-centric Subject-to-Image Synthesis. Yibin Wang, Weizhong Zhang, Jianwei Zheng, Cheng Jin. arXiv 2023. [PDF]Decompose and Realign: Tackling Condition Misalignment in Text-to-Image Diffusion Models. Luozhou Wang, Guibao Shen, Wenhang Ge, Guangyong Chen, Yijun Li, Ying-cong...
Use clip-retrieval to convert the images to embeddings. Use embedding-dataset-reordering to reorder the embeddings into the expected format. Usage: from dalle2_pytorch.dataloaders import ImageEmbeddingDataset, create_image_embedding_dataloader # Create a dataloader directly. dataloader = create_image_em...