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Found 5 papers, 4 papers with code
Deep Boosting Learning: A Brand-new Cooperative Approach for Image-Text Matching
Specifically, we propose a brand-new Deep Boosting Learning (DBL) algorithm, where an anchor branch is first trained to provide insights into the data properties, with a target branch gaining more advanced knowledge to develop optimal features and distance metrics.
Exploring Dynamic Transformer for Efficient Object Tracking
For instance, DyTrack obtains 64. 9% AUC on LaSOT with a speed of 256 fps.
UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory
Parameter-efficient transfer learning (PETL), i. e., fine-tuning a small portion of parameters, is an effective strategy for adapting pre-trained models to downstream domains.
Plug-and-Play Regulators for Image-Text Matching
Exploiting fine-grained correspondence and visual-semantic alignments has shown great potential in image-text matching.
Ranked #2 on
Image Retrieval
on Flickr30K 1K test
Similarity Reasoning and Filtration for Image-Text Matching
Image-text matching plays a critical role in bridging the vision and language, and great progress has been made by exploiting the global alignment between image and sentence, or local alignments between regions and words.
Ranked #3 on
Image Retrieval
on Flickr30K 1K test
