arXiv:2303.00721
공식 코드 · Papers with Code
Bootstrapping Parallel Anchors for Relative Representations
원문 초록
The use of relative representations for latent embeddings has shown potential in enabling latent space communication and zero-shot model stitching across a wide range of applications. Nevertheless, relative representations rely on a certain amount of parallel anchors to be given as input, which can be impractical to obtain in certain scenarios. To overcome this limitation, we propose an optimization-based method to discover new parallel anchors from a limited known set (seed). Our approach can be used to find semantic correspondence between different domains, align their relative spaces, and achieve competitive results in several tasks.
함께 살펴볼 논문
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Semantic Correspondence: Unified Benchmarking and a Strong Baseline
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Evaluation of Multilingual Image Captioning: How far can we get with CLIP models?
Multi-Level Correlation Network For Few-Shot Image Classification
CleanDIFT: Diffusion Features without Noise
Unleashing the Potential of the Diffusion Model in Few-shot Semantic Segmentation
토론
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