Cover Image

OmniSAM: Omnidirectional Segment Anything Model for UDA in Panoramic Semantic Segmentation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhong, Ding, Zheng, Xu, Liao, Chenfei, Lyu, Yuanhuiyi, Chen, Jialei, Wu, Shengyang, Zhang, Linfeng, Hu, Xuming
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

GoodSAM++: Bridging Domain and Capacity Gaps via Segment Anything Model for Panoramic Semantic Segmentation
by: Zhang, Weiming, et al.
Published: (2024)

Semantics, Distortion, and Style Matter: Towards Source-free UDA for Panoramic Segmentation
by: Zheng, Xu, et al.
Published: (2024)

Denoise and Align: Towards Source-Free UDA for Robust Panoramic Semantic Segmentation
by: Chang, Yaowen, et al.
Published: (2026)

GoodSAM: Bridging Domain and Capacity Gaps via Segment Anything Model for Distortion-aware Panoramic Semantic Segmentation
by: Zhang, Weiming, et al.
Published: (2024)

MAGIC++: Efficient and Resilient Modality-Agnostic Semantic Segmentation via Hierarchical Modality Selection
by: Zheng, Xu, et al.
Published: (2024)

Learning Modality-agnostic Representation for Semantic Segmentation from Any Modalities
by: Zheng, Xu, et al.
Published: (2024)

Understanding-in-Generation: Reinforcing Generative Capability of Unified Model via Infusing Understanding into Generation
by: Lyu, Yuanhuiyi, et al.
Published: (2025)

Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization
by: Zheng, Xu, et al.
Published: (2025)

PANORAMA: The Rise of Omnidirectional Vision in the Embodied AI Era
by: Zheng, Xu, et al.
Published: (2025)

360SFUDA++: Towards Source-free UDA for Panoramic Segmentation by Learning Reliable Category Prototypes
by: Zheng, Xu, et al.
Published: (2024)

Centering the Value of Every Modality: Towards Efficient and Resilient Modality-agnostic Semantic Segmentation
by: Zheng, Xu, et al.
Published: (2024)

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

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation
by: Zheng, Xu, et al.
Published: (2024)

OmniBind: Teach to Build Unequal-Scale Modality Interaction for Omni-Bind of All
by: Lyu, Yuanhuiyi, et al.
Published: (2024)

Are Multimodal Large Language Models Ready for Omnidirectional Spatial Reasoning?
by: Dongfang, Zihao, et al.
Published: (2025)

Image Anything: Towards Reasoning-coherent and Training-free Multi-modal Image Generation
by: Lyu, Yuanhuiyi, et al.
Published: (2024)

SAM 3: Segment Anything with Concepts
by: Carion, Nicolas, et al.
Published: (2025)

ClassWise-SAM-Adapter: Parameter Efficient Fine-tuning Adapts Segment Anything to SAR Domain for Semantic Segmentation
by: Pu, Xinyang, et al.
Published: (2024)

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

X-SAM: From Segment Anything to Any Segmentation
by: Wang, Hao, et al.
Published: (2025)

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

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

Char-SAM: Turning Segment Anything Model into Scene Text Segmentation Annotator with Character-level Visual Prompts
by: Xie, Enze, et al.
Published: (2024)

Benchmarking Multi-modal Semantic Segmentation under Sensor Failures: Missing and Noisy Modality Robustness
by: Liao, Chenfei, et al.
Published: (2025)

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

Black-box Targeted Adversarial Attack on Segment Anything (SAM)
by: Zheng, Sheng, et al.
Published: (2023)

SAM Audio: Segment Anything in Audio
by: Shi, Bowen, et al.
Published: (2025)

UV-SAM: Adapting Segment Anything Model for Urban Village Identification
by: Zhang, Xin, et al.
Published: (2024)

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)

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

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

I-MedSAM: Implicit Medical Image Segmentation with Segment Anything
by: Wei, Xiaobao, et al.
Published: (2023)

Open Panoramic Segmentation
by: Zheng, Junwei, et al.
Published: (2024)

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

SAM4D: Segment Anything in Camera and LiDAR Streams
by: Xu, Jianyun, et al.
Published: (2025)

Don't Just Chase "Highlighted Tokens" in MLLMs: Revisiting Visual Holistic Context Retention
by: Zou, Xin, et al.
Published: (2025)

RealRAG: Retrieval-augmented Realistic Image Generation via Self-reflective Contrastive Learning
by: Lyu, Yuanhuiyi, et al.
Published: (2025)

DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation
by: Gao, Yifan, et al.
Published: (2023)