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Segment Anything Model (SAM) has garnered significant attention in segmentation tasks due to their zero-shot generalization ability.
“Microsoft coco: Common objects in context,”
Lin et al., · 2014
Earlier work this paper cites.
U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger et al., · 2015
Earlier work this paper cites.
“Distilling the knowledge in a neural network,”
Hinton et al., · 2015
Earlier work this paper cites.
“Lvis: A dataset for large vocabulary instance segmentation,”
Gupta et al., · 2019
Earlier work this paper cites.
“MMDetection: Open mmlab detection toolbox and benchmark,”
Chen et al., · 2019
Earlier work this paper cites.
“Tinyvit: Fast pretraining distillation for small vision transformers,”
Wu et al., · 2022
Earlier work this paper cites.
“Flashattention: Fast and memory-efficient exact attention with io-awareness,”
Dao et al., · 2022
Earlier work this paper cites.
“Show, attend and distill:knowledge distillation via attention-based feature matching,”
Ji et al., · 2022
Cited alongside, same era.
Kirillov et al., · 2023
Cited alongside, same era.
“Segment anything for microscopy,”
Archit et al., · 2023
Cited alongside, same era.
“Segment anything in medical images,”
Ma et al., · 2023
Cited alongside, same era.
Cheng et al., · 2023
Cited alongside, same era.
“Track anything: Segment anything meets videos,”
Yang et al., · 2023
Cited alongside, same era.
Zhao et al., · 2023
Later among the works it cites.
“Faster segment anything: Towards lightweight sam for mobile applications,”
Zhang et al., · 2023
Later among the works it cites.
“Efficientsam: Leveraged masked image pretraining for efficient segment anything,”
Xiong et al., · 2023
Later among the works it cites.
“Accelerating generative ai,” accelerating-generative-ai , 2023
PyTorch Team, · 2023
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“Ultralytics yolov8,” 2023
Jocher et al., · 2023
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“Anything-3d: Towards single-view anything reconstruction in the wild,”
Shen et al., · 2023
Cited alongside, same era.
Dao, · 2023
Later among the works it cites.
“Seggpt: Segmenting everything in context,”
Wang et al., · 2023
Later among the works it cites.