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Neural Matching Fields: Implicit Representation of Matching Fields for Visual Correspondence.

, , , , , , and . NeurIPS, (2022)

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Pose-Diversified Augmentation with Diffusion Model for Person Re-Identification., , , , , , , , , and 1 other author(s). CoRR, (2024)CATs++: Boosting Cost Aggregation With Convolutions and Transformers., , and . IEEE Trans. Pattern Anal. Mach. Intell., 45 (6): 7174-7194 (June 2023)CATs: Cost Aggregation Transformers for Visual Correspondence., , , , , and . NeurIPS, page 9011-9023. (2021)MIDMs: Matching Interleaved Diffusion Models for Exemplar-Based Image Translation., , , , and . AAAI, page 2191-2199. AAAI Press, (2023)LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data., , , , , , and . CVPR, page 23401-23411. IEEE, (2023)MIDMs: Matching Interleaved Diffusion Models for Exemplar-based Image Translation., , , , and . CoRR, (2022)Integrative Feature and Cost Aggregation with Transformers for Dense Correspondence., , , and . CoRR, (2022)Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation., , , , and . ECCV (29), volume 13689 of Lecture Notes in Computer Science, page 108-126. Springer, (2022)DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation., , , , , , and . NeurIPS, (2023)Neural Matching Fields: Implicit Representation of Matching Fields for Visual Correspondence., , , , , , and . NeurIPS, (2022)