Learning Sample-wise Rank-aware Interpolation Weights for Composed Visual Data Retrieval
This work revisits the efficacy of simple linear interpolation within an embedding space, and introduces SRAIN, the first framework that dynamically predicts query-specific interpolation weights, and achieves the best in composed video retrieval and matches the current state of the art in composed image retrieval.