Papers Distance regression
“Distance regression” 태그가 달린 논문 23편 · 필터 해제
SparseOcc++: Geometry-Aware Sparse Latent Representation for Semantic Occupancy Prediction
Vision-based 3D semantic occupancy prediction is essential for autonomous driving, yet dense voxel representations waste computation on largely empty space, while BEV and TPV projections compromise fine-grained 3D struct…
Semantic SegmentationDistance regressionAutonomous DrivingRedefining Quality Criteria and Distance-Aware Score Modeling for Image Editing Assessment
Recent advances in image editing have heightened the need for reliable Image Editing Quality Assessment (IEQA). Unlike traditional methods, IEQA requires complex reasoning over multimodal inputs and multi-dimensional ass…
Distance regressionImage EditingTemporal Zoom Networks: Distance Regression and Continuous Depth for Efficient Action Localization
Temporal action localization requires both precise boundary detection and computational efficiency. Current methods apply uniform computation across all temporal positions, wasting resources on easy boundaries while stru…
Temporal Action LocalizationComputational EfficiencyKnowledge DistillationDistance regressionOvercoming error-in-variable problem in data-driven model discovery by orthogonal distance regression
Despite the recent proliferation of machine learning methods like SINDy that promise automatic discovery of governing equations from time-series data, there remain significant challenges to discovering models from noisy …
Distance regressionCHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning
Advances in graph machine learning (ML) have been driven by applications in chemistry as graphs have remained the most expressive representations of molecules. While early graph ML methods focused primarily on small orga…
Atomic number classificationBenchmarkingCrystal system classificationDistance regression+9Approaches to biological species delimitation based on genetic and spatial dissimilarity
The delimitation of biological species, i.e., deciding which individuals belong to the same species and whether and how many different species are represented in a data set, is key to the conservation of biodiversity. Mu…
Distance regressionregressionDistFormer: Enhancing Local and Global Features for Monocular Per-Object Distance Estimation
Accurate per-object distance estimation is crucial in safety-critical applications such as autonomous driving, surveillance, and robotics. Existing approaches rely on two scales: local information (i.e., the bounding box…
Autonomous DrivingDecoderDistance regressionObjectScalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More
The current best practice for computing optimal transport (OT) is via entropy regularization and Sinkhorn iterations. This algorithm runs in quadratic time as it requires the full pairwise cost matrix, which is prohibiti…
Distance regressionA Coarse-to-Fine Instance Segmentation Network with Learning Boundary Representation
Boundary-based instance segmentation has drawn much attention since of its attractive efficiency. However, existing methods suffer from the difficulty in long-distance regression. In this paper, we propose a coarse-to-fi…
Distance regressionInstance SegmentationregressionSemantic SegmentationMulti-task fully convolutional network for tree species mapping in dense forests using small training hyperspectral data
This work proposes a multi-task fully convolutional architecture for tree species mapping in dense forests from sparse and scarce polygon-level annotations using hyperspectral UAV-borne data. Our model implements a parti…
Distance regressionregressionSegmentationSemantic SegmentationCardiac Segmentation on CT Images through Shape-Aware Contour Attentions
Cardiac segmentation of atriums, ventricles, and myocardium in computed tomography (CT) images is an important first-line task for presymptomatic cardiovascular disease diagnosis. In several recent studies, deep learning…
Cardiac SegmentationComputed Tomography (CT)Distance regressionHeart Segmentation+4Composite Localization for Human Pose Estimation
The existing human pose estimation methods are confronted with inaccurate long-distance regression or high computational cost due to the complex learning objectives. This work proposes a novel deep learning framework for…
Distance regressionPose EstimationPixel-wise Distance Regression for Glacier Calving Front Detection and Segmentation
Glacier calving front position (CFP) is an important glaciological variable. Traditionally, delineating the CFPs has been carried out manually, which was subjective, tedious and expensive. Automating this process is cruc…
Distance regressionregressionWarpspeed Computation of Optimal Transport, Graph Distances, and Embedding Alignment
Optimal transport (OT) is a cornerstone of many machine learning tasks. The current best practice for computing OT is via entropy regularization and Sinkhorn iterations. This algorithm runs in quadratic time and requires…
Distance regressionNeural Network-based Acoustic Vehicle Counting
This paper addresses acoustic vehicle counting using one-channel audio. We predict the pass-by instants of vehicles from local minima of clipped vehicle-to-microphone distance. This distance is predicted from audio using…
Distance regressionregressionRadar-Camera Sensor Fusion for Joint Object Detection and Distance Estimation in Autonomous Vehicles
In this paper we present a novel radar-camera sensor fusion framework for accurate object detection and distance estimation in autonomous driving scenarios. The proposed architecture uses a middle-fusion approach to fuse…
2D Object DetectionAutonomous DrivingAutonomous VehiclesDistance regression+5Improving Pixel Embedding Learning through Intermediate Distance Regression Supervision for Instance Segmentation
As a proposal-free approach, instance segmentation through pixel embedding learning and clustering is gaining more emphasis. Compared with bounding box refinement approaches, such as Mask R-CNN, it has potential advantag…
ClusteringDistance regressionInstance Segmentationregression+2EOLO: Embedded Object Segmentation only Look Once
In this paper, we introduce an anchor-free and single-shot instance segmentation method, which is conceptually simple with 3 independent branches, fully convolutional and can be used by easily embedding it into mobile an…
Distance regressionGPUInstance SegmentationObject+3Pose-Aware Instance Segmentation Framework from Cone Beam CT Images for Tooth Segmentation
Individual tooth segmentation from cone beam computed tomography (CBCT) images is an essential prerequisite for an anatomical understanding of orthodontic structures in several applications, such as tooth reformation pla…
Distance regressionImage AugmentationImage CroppingInstance Segmentation+4PolarMask: Single Shot Instance Segmentation with Polar Representation
In this paper, we introduce an anchor-box free and single shot instance segmentation method, which is conceptually simple, fully convolutional and can be used as a mask prediction module for instance segmentation, by eas…
Distance regressionInstance SegmentationObject Detectionregression+2