computer-vision-5
Generalized Referring Expression Segmentation
3260 papers • 126 benchmarks • 313 datasets
Generalized Referring Expression Segmentation (GRES), introduced by Liu et al in CVPR 2023, allows expressions indicating any number of target objects. GRES takes an image and a referring expression as input, and requires mask prediction of the target object(s).
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GRES: Generalized Referring Expression Segmentation
Henghui Ding, Chang Liu, Xudong Jiang•Wed May 31 2023
A region-based GRES baseline ReLA is proposed that adaptively divides the image into regions with subinstance clues, and explicitly models the region-region and region-language dependencies and achieves new state-of-the-art performance on the both newly proposed GRES and classic RES tasks.
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