Papers Object Localization
“Object Localization” 태그가 달린 논문 726편 · 필터 해제
ROML: A Robust Feature Correspondence Approach for Matching Objects in A Set of Images
Feature-based object matching is a fundamental problem for many applications in computer vision, such as object recognition, 3D reconstruction, tracking, and motion segmentation. In this work, we consider simultaneously …
3D ReconstructionDistributed OptimizationMotion SegmentationObject+2Multi-View Priors for Learning Detectors from Sparse Viewpoint Data
While the majority of today's object class models provide only 2D bounding boxes, far richer output hypotheses are desirable including viewpoint, fine-grained category, and 3D geometry estimate. However, models trained t…
3D geometryObjectObject LocalizationTransfer Learning+1Associative embeddings for large-scale knowledge transfer with self-assessment
We propose a method for knowledge transfer between semantically related classes in ImageNet. By transferring knowledge from the images that have bounding-box annotations to the others, our method is capable of automatica…
Gaussian ProcessesObject LocalizationTransfer LearningMaximum Cohesive Grid of Superpixels for Fast Object Localization
This paper addresses a challenging problem of regularizing arbitrary superpixels into an optimal grid structure, which may significantly extend current low-level vision algorithms by allowing them to use superpixels (SPs…
ObjectObject LocalizationSuperpixelsMax-Margin Structured Output Regression for Spatio-Temporal Action Localization
Structured output learning has been successfully applied to object localization, where the mapping between an image and an object bounding box can be well captured. Its extension to action localization in videos, however…
Action LocalizationObject LocalizationregressionSpatio-Temporal Action Localization+1Self-Paced Learning for Latent Variable Models
Latent variable models are a powerful tool for addressing several tasks in machine learning. However, the algorithms for learning the parameters of latent variable models are prone to getting stuck in a bad local optimum…
Handwritten Digit RecognitionObject Localization