Cover Image

SAM2RL: Towards Reinforcement Learning Memory Control in Segment Anything Model 2

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Adamyan, Alen, Čížek, Tomáš, Straka, Matej, Janouskova, Klara, Schmid, Martin
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Koo-Fu CLIP: Closed-Form Adaptation of Vision-Language Models via Fukunaga-Koontz Linear Discriminant Analysis
by: Suchanek, Matej, et al.
Published: (2026)

SAM 2: Segment Anything in Images and Videos
by: Ravi, Nikhila, et al.
Published: (2024)

AM-SAM: Automated Prompting and Mask Calibration for Segment Anything Model
by: Li, Yuchen, et al.
Published: (2024)

MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation
by: Liao, Chenfei, et al.
Published: (2025)

Single Image Test-Time Adaptation for Segmentation
by: Janouskova, Klara, et al.
Published: (2023)

From SAM to SAM 2: Exploring Improvements in Meta's Segment Anything Model
by: Geetha, Athulya Sundaresan, et al.
Published: (2024)

StructSAM: Structure- and Spectrum-Preserving Token Merging for Segment Anything Models
by: Nguyen, Duy M. H., et al.
Published: (2026)

PTQ4SAM: Post-Training Quantization for Segment Anything
by: Lv, Chengtao, et al.
Published: (2024)

DeiSAM: Segment Anything with Deictic Prompting
by: Shindo, Hikaru, et al.
Published: (2024)

AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization
by: Zhang, Wenlun, et al.
Published: (2025)

AlignSAM: Aligning Segment Anything Model to Open Context via Reinforcement Learning
by: Huang, Duojun, et al.
Published: (2024)

RemoteSAM: Towards Segment Anything for Earth Observation
by: Yao, Liang, et al.
Published: (2025)

Atlas-Assisted Segment Anything Model for Fetal Brain MRI (FeTal-SAM)
by: Zeng, Qi, et al.
Published: (2026)

Evaluation of Segment Anything Model 2: The Role of SAM2 in the Underwater Environment
by: Lian, Shijie, et al.
Published: (2024)

Medical SAM 2: Segment medical images as video via Segment Anything Model 2
by: Zhu, Jiayuan, et al.
Published: (2024)

Bringing the Context Back into Object Recognition, Robustly
by: Janouskova, Klara, et al.
Published: (2024)

Robust Context-Aware Object Recognition
by: Janouskova, Klara, et al.
Published: (2025)

RepViT-SAM: Towards Real-Time Segmenting Anything
by: Wang, Ao, et al.
Published: (2023)

EfficientViT-SAM: Accelerated Segment Anything Model Without Accuracy Loss
by: Zhang, Zhuoyang, et al.
Published: (2024)

Biomedical SAM 2: Segment Anything in Biomedical Images and Videos
by: Yan, Zhiling, et al.
Published: (2024)

Q-SAM2: Accurate Quantization for Segment Anything Model 2
by: Farronato, Nicola, et al.
Published: (2025)

SAM-OCTA2: Layer Sequence OCTA Segmentation with Fine-tuned Segment Anything Model 2
by: Chen, Xinrun, et al.
Published: (2024)

Multimodal Large Language Models as Image Classifiers
by: Kisel, Nikita, et al.
Published: (2026)

A Distractor-Aware Memory for Visual Object Tracking with SAM2
by: Videnovic, Jovana, et al.
Published: (2024)

RMP-SAM: Towards Real-Time Multi-Purpose Segment Anything
by: Xu, Shilin, et al.
Published: (2024)

Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation
by: Ye, Maoyuan, et al.
Published: (2024)

SAM2-LOVE: Segment Anything Model 2 in Language-aided Audio-Visual Scenes
by: Wang, Yuji, et al.
Published: (2025)

Det-SAM2:Technical Report on the Self-Prompting Segmentation Framework Based on Segment Anything Model 2
by: Wang, Zhiting, et al.
Published: (2024)

FusionSAM: Visual Multi-Modal Learning with Segment Anything
by: Li, Daixun, et al.
Published: (2024)

Compress Any Segment Anything Model (SAM)
by: Fan, Juntong, et al.
Published: (2025)

SAM3-I: Segment Anything with Instructions
by: Li, Jingjing, et al.
Published: (2025)

PaveSAM Segment Anything for Pavement Distress
by: Owor, Neema Jakisa, et al.
Published: (2024)

BiSeg-SAM: Weakly-Supervised Post-Processing Framework for Boosting Binary Segmentation in Segment Anything Models
by: Su, Encheng, et al.
Published: (2025)

A Multispectral Automated Transfer Technique (MATT) for machine-driven image labeling utilizing the Segment Anything Model (SAM)
by: Gallagher, James E., et al.
Published: (2024)

TinySAM: Pushing the Envelope for Efficient Segment Anything Model
by: Shu, Han, et al.
Published: (2023)

SAQ-SAM: Semantically-Aligned Quantization for Segment Anything Model
by: Zhang, Jing, et al.
Published: (2025)

pFedSAM: Personalized Federated Learning of Segment Anything Model for Medical Image Segmentation
by: Wang, Tong, et al.
Published: (2025)

OmniSAM: Omnidirectional Segment Anything Model for UDA in Panoramic Semantic Segmentation
by: Zhong, Ding, et al.
Published: (2025)

Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
by: Wu, Junde, et al.
Published: (2023)

SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation
by: Xiong, Xinyu, et al.
Published: (2024)