Zero Shot Segmentation


Zero-shot segmentation is the process of segmenting objects in images without using any labeled data.

ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features

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Feb 06, 2025
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ZISVFM: Zero-Shot Object Instance Segmentation in Indoor Robotic Environments with Vision Foundation Models

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Feb 05, 2025
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Fine-grained Preference Optimization Improves Zero-shot Text-to-Speech

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Feb 05, 2025
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IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning

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Feb 04, 2025
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RFMedSAM 2: Automatic Prompt Refinement for Enhanced Volumetric Medical Image Segmentation with SAM 2

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Feb 04, 2025
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Scalable, Training-Free Visual Language Robotics: A Modular Multi-Model Framework for Consumer-Grade GPUs

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Feb 03, 2025
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Vision and Language Reference Prompt into SAM for Few-shot Segmentation

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Feb 02, 2025
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AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis

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Feb 03, 2025
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FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM

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Jan 31, 2025
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CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation

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Jan 27, 2025
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