Papers Interactive Segmentation
“Interactive Segmentation” 태그가 달린 논문 306편 · 필터 해제
TAGS: 3D Tumor-Adaptive Guidance for SAM
Foundation models (FMs) such as CLIP and SAM have recently shown great promise in image segmentation tasks, yet their adaptation to 3D medical imaging-particularly for pathology detection and segmentation-remains underex…
AnatomyImage SegmentationInteractive SegmentationMedical Image Segmentation+3iSegMan: Interactive Segment-and-Manipulate 3D Gaussians
The efficient rendering and explicit nature of 3DGS promote the advancement of 3D scene manipulation. However, existing methods typically encounter challenges in controlling the manipulation region and are unable to furn…
3DGSInteractive SegmentationSegmentationMAIS: Memory-Attention for Interactive Segmentation
Interactive medical segmentation reduces annotation effort by refining predictions through user feedback. Vision Transformer (ViT)-based models, such as the Segment Anything Model (SAM), achieve state-of-the-art performa…
Interactive SegmentationSegmentationBenchmarking Feature Upsampling Methods for Vision Foundation Models using Interactive Segmentation
Vision Foundation Models (VFMs) are large-scale, pre-trained models that serve as general-purpose backbones for various computer vision tasks. As VFMs' popularity grows, there is an increasing interest in understanding t…
BenchmarkingFeature UpsamplingInteractive SegmentationScene UnderstandingMoSAM: Motion-Guided Segment Anything Model with Spatial-Temporal Memory Selection
The recent Segment Anything Model 2 (SAM2) has demonstrated exceptional capabilities in interactive object segmentation for both images and videos. However, as a foundational model on interactive segmentation, SAM2 perfo…
Instance SegmentationInteractive SegmentationObjectObject Tracking+5DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency
Given a single labeled example, in-context segmentation aims to segment corresponding objects. This setting, known as one-shot segmentation in few-shot learning, explores the segmentation model's generalization ability a…
Few-Shot LearningInteractive SegmentationOne-Shot SegmentationScene Understanding+6Easy3D: A Simple Yet Effective Method for 3D Interactive Segmentation
The increasing availability of digital 3D environments, whether through image-based 3D reconstruction, generation, or scans obtained by robots, is driving innovation across various applications. These come with a signifi…
3D ReconstructionDecoderInteractive SegmentationBenchmark of Segmentation Techniques for Pelvic Fracture in CT and X-ray: Summary of the PENGWIN 2024 Challenge
The segmentation of pelvic fracture fragments in CT and X-ray images is crucial for trauma diagnosis, surgical planning, and intraoperative guidance. However, accurately and efficiently delineating the bone fragments rem…
AnatomyBenchmarkingInteractive SegmentationSegmentationRefCut: Interactive Segmentation with Reference Guidance
Interactive segmentation aims to segment the specified target on the image with positive and negative clicks from users. Interactive ambiguity is a crucial issue in this field, which refers to the possibility of multiple…
Interactive SegmentationObjectM2N2V2: Multi-Modal Unsupervised and Training-free Interactive Segmentation
We present Markov Map Nearest Neighbor V2 (M2N2V2), a novel and simple, yet effective approach which leverages depth guidance and attention maps for unsupervised and training-free point-prompt-based interactive segmentat…
Interactive SegmentationROS-SAM: High-Quality Interactive Segmentation for Remote Sensing Moving Object
The availability of large-scale remote sensing video data underscores the importance of high-quality interactive segmentation. However, challenges such as small object sizes, ambiguous features, and limited generalizatio…
Domain AdaptationInteractive SegmentationObject TrackingSegmentationnnInteractive: Redefining 3D Promptable Segmentation
Accurate and efficient 3D segmentation is essential for both clinical and research applications. While foundation models like SAM have revolutionized interactive segmentation, their 2D design and domain shift limitations…
BenchmarkingInteractive SegmentationSegmentationSegAgent: Exploring Pixel Understanding Capabilities in MLLMs by Imitating Human Annotator Trajectories
While MLLMs have demonstrated adequate image understanding capabilities, they still struggle with pixel-level comprehension, limiting their practical applications. Current evaluation tasks like VQA and visual grounding r…
Decision MakingInteractive SegmentationReferring Expression SegmentationSegmentation+3SegAgent: Exploring Pixel Understanding Capabilities in MLLMs by Imitating Human Annotator Trajectories
While MLLMs have demonstrated adequate image understanding capabilities, they still struggle with pixel-level comprehension, limiting their practical applications. Current evaluation tasks like VQA and visual grounding r…
Decision MakingInteractive SegmentationSegmentationVisual Grounding+2Continuous Online Adaptation Driven by User Interaction for Medical Image Segmentation
Interactive segmentation models use real-time user interactions, such as mouse clicks, as extra inputs to dynamically refine the model predictions. After model deployment, user corrections of model predictions could be u…
Image SegmentationInteractive SegmentationMedical Image SegmentationSegmentation+1Interactive Segmentation and Report Generation for CT Images
Automated CT report generation plays a crucial role in improving diagnostic accuracy and clinical workflow efficiency. However, existing methods lack interpretability and impede patient-clinician understanding, while the…
AttributeDiagnosticInteractive SegmentationLesion Segmentation+1Text-promptable Propagation for Referring Medical Image Sequence Segmentation
Medical image sequences, generated by both 2D video-based examinations and 3D imaging techniques, consist of sequential frames or slices that capture the same anatomical entities (e.g., organs or lesions) from multiple p…
Interactive SegmentationSegmentationTowards Fine-grained Interactive Segmentation in Images and Videos
The recent Segment Anything Models (SAMs) have emerged as foundational visual models for general interactive segmentation. Despite demonstrating robust generalization abilities, they still suffer performance degradations…
Interactive SegmentationSegmentationSegment Anything for Histopathology
Nucleus segmentation is an important analysis task in digital pathology. However, methods for automatic segmentation often struggle with new data from a different distribution, requiring users to manually annotate nuclei…
Image SegmentationInstance SegmentationInteractive SegmentationSegmentation+1Let Human Sketches Help: Empowering Challenging Image Segmentation Task with Freehand Sketches
Sketches, with their expressive potential, allow humans to convey the essence of an object through even a rough contour. For the first time, we harness this expressive potential to improve segmentation performance in cha…
Image SegmentationInteractive SegmentationObjectobject-detection+3