Papers Instance Segmentation
“Instance Segmentation” 태그가 달린 논문 2,537편 · 필터 해제
GTR: Gated Token Recurrence for Efficient Dense Prediction
Self-attention-based vision backbones perform well on dense prediction, but the quadratic computational cost of global softmax attention limits their efficiency as image resolution increases. We introduce Gated Token Rec…
Monocular Depth EstimationInstance SegmentationSemantic SegmentationPose EstimationAccelerated Decoding of Centroid Positional Encoding for Instance Segmentation
Beyond model inference, the decoding stage, which converts raw network outputs into task-level representations, constitutes a significant portion of the execution cost. Despite its practical impact, prediction decoding h…
Instance SegmentationChannel-Wise and Token-Aware Post-Training Quantization for Visual State Space Duality
State space models (SSMs), particularly Mamba, have emerged as efficient alternatives to attention-based architectures and have been extended to vision through ViM, VMamba, and Visual State Space Duality (VSSD). Yet the …
Semantic SegmentationInstance SegmentationObject DetectionTAPe+ML: A Compact Structured Representation for Multi-Task Computer Vision
We present TAPe+ML v3, a compact computer vision system based on TAPe (Theory of Active Perception), a structured representation that encodes relations among perceptual elements before recognition. Instead of operating d…
Instance SegmentationImage ClassificationObject LocalizationObject DetectionCedarCypress3D: an annotated UAV-LiDAR dataset of individual trees in planted cedar and cypress forests
Individual tree measurements derived from Light Detection and Ranging (LiDAR) mounted on Unmanned Aerial Vehicles (UAV) provide valuable information for forest inventory, ecosystem monitoring, and sustainable forest mana…
Instance SegmentationSemantic SegmentationPoint CloudsQCell: Recombining and Aligning Cell Queries for Overlapping Instance Segmentation
Instance segmentation of overlapping cells in microscopy remains challenging due to semi-transparent structures that produce weak boundaries and mixed visual evidence in overlap regions. Existing methods address this thr…
Instance SegmentationCell SegmentationQuality Inspection of Printed Circuit Board Pin Insertion via Semantic Segmentation and Board-Level Feature Extraction
Quality control during printed circuit board (PCB) assembly is a critical step in ensuring reliable electronic products. Detecting misaligned pins during or after pin insertion remains a particularly challenging inspecti…
Instance SegmentationSemantic SegmentationAnomaly DetectionHarvestPoint-ACT: Explicit Target Selection and Harvest-Point Conditioning for Robotic Fruit Harvesting under Occlusion
End-to-end imitation learning avoids hand-made robot motion for approaching and grasping, but the policy must still decide which fruit to pick and where to close the gripper. Occlusion can make the policy lose the select…
Instance SegmentationTEAMS: Text-prompted spatiotEmporal dual-heAd Mamba Snake
Deep snake is a promising family of instance segmentation methods that accurately predicts object-level contours, thereby overcoming common pixel-level misclassification issues such as mask cavities and jagged edges in s…
Medical Image SegmentationInstance SegmentationSemantic SegmentationUnsupervised Learning of Cell Instances with Generative Routing Pyramids
Identifying and representing object instances such as cells or nuclei is a common task in microscopy image analysis. Established machine learning workflows typically use supervised detection or segmentation followed by f…
Instance SegmentationPredicting Signed Distance Functions for Visual Instance Segmentation
Visual instance segmentation is a challenging problem and becomes even more difficult if objects of interest varies unconstrained in shape. Some objects are well described by a rectangle, however, this is hardly always t…
Instance SegmentationHear to See: Discerning Stateful Listening for Audio-Visual Instance Segmentation
Audio-visual instance segmentation (AVIS) requires accurately identifying and tracking individual sounding objects with pixel-level masks. Existing methods struggle to match overlapping acoustic events with visual instan…
Instance SegmentationTwo-Stage Teacher-Student Reliable Prior Learning for Robust Underwater Image Enhancement
Underwater image enhancement (UIE) aims to recover clear images from observations affected by wavelength-dependent absorption, scattering, and spatially nonuniform degradation. Although existing generative methods can ha…
Instance SegmentationImage EnhancementObject DetectionZMIS-SAM: Segment Anything Model Enhanced with Wavelet Transform for Zooplankton Microscopy Image Instance Segmentation
As primary consumers in the marine food chain, zooplankton play a crucial role in maintaining marine ecological balance. However, the Segment Anything Model (SAM) exhibits limited performance in microscopic image instanc…
Instance SegmentationMixFrag: Fragility-Guided Mixed-Precision Post-Training Quantization for Vision Transformers
Post-training quantization (PTQ) has emerged as an effective solution for deploying Vision Transformers (ViTs) on resource-constrained devices. However, existing PTQ methods typically employ uniform bit-widths across tra…
Instance SegmentationObject DetectionThe LAIA Dataset: Labelled Attention for Intelligent Automobiles
The development of autonomous vehicles (AVs) usually relies heavily on data-driven artificial intelligence (AI) models that require large volumes of sensor data with ground-truth annotations. While modular architectures …
Instance SegmentationAutonomous VehiclesHyperImageNet: A Large-Scale High-Spatial Resolution Hyperspectral Imagery Classification Benchmark
We present HyperImageNet, a large-scale benchmark for fine-grained hyperspectral land-cover understanding. The dataset contains 26,084 airborne hyperspectral image patches with 224 spectral bands and 138 fine-grained lan…
Instance SegmentationStill image and spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels
In this manuscript we release two datasets for visual sensing of tomato plants grown in commercial-like settings and acquired using a robot. The first is BUTom21 which consists of still images and manual annotations. The…
Instance SegmentationThe GEST-Engine: From Event Graphs to Synthetic Video. A Full Technical Report
We present the GEST-Engine, a complete system that goes from natural-language text to fully-annotated multi-actor video. At its core is an explicit world model: rather than encoding state as a learned latent, the engine …
Instance SegmentationPromptable Concept Segmentation from Above: Evaluating SAM 3's Zero-Shot and One-Shot Capabilities in Remote Sensing
The deployment of large-scale foundation models, such as the Segment Anything Model 3 (SAM 3), promises a transition toward open-vocabulary, training-free computer vision. However, their capacity to generalize out-of-dis…
Instance SegmentationScene ClassificationObject Detection