Papers Object Segmentation
“Object Segmentation” 태그가 달린 논문 86편 · 필터 해제
From Unstable to Playable: Stabilizing Angry Birds Levels via Object Segmentation
Procedural Content Generation (PCG) techniques enable automatic creation of diverse and complex environments. While PCG facilitates more efficient content creation, ensuring consistently high-quality, industry-standard c…
Object SegmentationPANICL: Mitigating Over-Reliance on Single Prompt in Visual In-Context Learning
Visual In-Context Learning (VICL) uses input-output image pairs, referred to as in-context pairs (or examples), as prompts alongside query images to guide models in performing diverse vision tasks. However, VICL often su…
Object SegmentationKeypoint DetectionObject DetectionUniMRSeg: Unified Modality-Relax Segmentation via Hierarchical Self-Supervised Compensation
Multi-modal image segmentation faces real-world deployment challenges from incomplete/corrupted modalities degrading performance. While existing methods address training-inference modality gaps via specialized per-combin…
Brain Tumor SegmentationSemantic SegmentationContrastive LearningObject SegmentationDyGLNet: Hybrid Global-Local Feature Fusion with Dynamic Upsampling for Medical Image Segmentation
Medical image segmentation grapples with challenges including multi-scale lesion variability, ill-defined tissue boundaries, and computationally intensive processing demands. This paper proposes the DyGLNet, which achiev…
Medical Image SegmentationObject SegmentationWorld Modeling with Probabilistic Structure Integration
We present Probabilistic Structure Integration (PSI), a system for learning richly controllable and flexibly promptable world models from data. PSI consists of a three-step cycle. The first step, Probabilistic prediction…
Object SegmentationCausal InferenceVideo PredictionPoint Linguist Model: Segment Any Object via Bridged Large 3D-Language Model
3D object segmentation with Large Language Models (LLMs) has become a prevailing paradigm due to its broad semantics, task flexibility, and strong generalization. However, this paradigm is hindered by representation misa…
Object SegmentationPoint CloudsSOPSeg: Prompt-based Small Object Instance Segmentation in Remote Sensing Imagery
Extracting small objects from remote sensing imagery plays a vital role in various applications, including urban planning, environmental monitoring, and disaster management. While current research primarily focuses on sm…
Zero-shot GeneralizationSmall Object DetectionInstance SegmentationObject SegmentationM3DMap: Object-aware Multimodal 3D Mapping for Dynamic Environments
3D mapping in dynamic environments poses a challenge for modern researchers in robotics and autonomous transportation. There are no universal representations for dynamic 3D scenes that incorporate multimodal data such as…
Object SegmentationPoint CloudsRynnEC: Bringing MLLMs into Embodied World
We introduce RynnEC, a video multimodal large language model designed for embodied cognition. Built upon a general-purpose vision-language foundation model, RynnEC incorporates a region encoder and a mask decoder, enabli…
Object SegmentationSpatial ReasoningRPCANet++: Deep Interpretable Robust PCA for Sparse Object Segmentation
Robust principal component analysis (RPCA) decomposes an observation matrix into low-rank background and sparse object components. This capability has enabled its application in tasks ranging from image restoration to se…
Object SegmentationImage RestorationZero-shot Shape Classification of Nanoparticles in SEM Images using Vision Foundation Models
Accurate and efficient characterization of nanoparticle morphology in Scanning Electron Microscopy (SEM) images is critical for ensuring product quality in nanomaterial synthesis and accelerating development. However, co…
Object SegmentationEnhancing Object Discovery for Unsupervised Instance Segmentation and Object Detection
We propose Cut-Once-and-LEaRn (COLER), a simple approach for unsupervised instance segmentation and object detection. COLER first uses our developed CutOnce to generate coarse pseudo labels, then enables the detector to …
Unsupervised Instance SegmentationUnsupervised Object LocalizationObject SegmentationObject DetectionSAMPO-Path: Segmentation Intent-Aligned Preference Optimization for Pathology Foundation Model Segmentation
Foundation models have shown strong performance in multi-object segmentation with visual prompts, yet histopathology images remain challenging due to high cellular density, heterogeneity, and the gap between pixel-level …
Object SegmentationPointGauss: Point Cloud-Guided Multi-Object Segmentation for Gaussian Splatting
We introduce PointGauss, a novel point cloud-guided framework for real-time multi-object segmentation in Gaussian Splatting representations. Unlike existing methods that suffer from prolonged initialization and limited m…
Point Cloud SegmentationComputational EfficiencyObject SegmentationMergeSAM: Unsupervised change detection of remote sensing images based on the Segment Anything Model
Recently, large foundation models trained on vast datasets have demonstrated exceptional capabilities in feature extraction and general feature representation. The ongoing advancements in deep learning-driven large model…
Object SegmentationChange DetectionObject-centric Video Question Answering with Visual Grounding and Referring
Video Large Language Models (VideoLLMs) have recently demonstrated remarkable progress in general video understanding. However, existing models primarily focus on high-level comprehension and are limited to text-only res…
Video Question AnsweringObject SegmentationVisual GroundingObject segmentation in the wild with foundation models: application to vision assisted neuro-prostheses for upper limbs
In this work, we address the problem of semantic object segmentation using foundation models. We investigate whether foundation models, trained on a large number and variety of objects, can perform object segmentation wi…
Object SegmentationRobust Noisy Pseudo-label Learning for Semi-supervised Medical Image Segmentation Using Diffusion Model
Obtaining pixel-level annotations in the medical domain is both expensive and time-consuming, often requiring close collaboration between clinical experts and developers. Semi-supervised medical image segmentation aims t…
Semi-supervised Medical Image SegmentationObject Segmentationrt-RISeg: Real-Time Model-Free Robot Interactive Segmentation for Active Instance-Level Object Understanding
Successful execution of dexterous robotic manipulation tasks in new environments, such as grasping, depends on the ability to proficiently segment unseen objects from the background and other objects. Previous works in u…
Unseen Object Instance SegmentationInteractive SegmentationObject SegmentationSAM2RL: Towards Reinforcement Learning Memory Control in Segment Anything Model 2
Segment Anything Model 2 (SAM 2) has demonstrated strong performance in object segmentation tasks and has become the state-of-the-art for visual object tracking. The model stores information from previous frames in a mem…
Reinforcement LearningVisual Object TrackingObject Segmentation