Finding nemo: Deformable object class modelling using curve matching

By Mukta Prasad, Andrew William Fitzgibbon, Andrew Zisserman, Luc Van Gool. 2010

29 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computational Mechanics, Computer Vision and Pattern Recognition

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Citations in the corpus

Lifting Object Detection Datasets into 3D (2015, positive): “To account for differences between the 3D exemplars and the object depicted, Su and Guibas [26] choose a few exemplars that appear to be similar to the depicted shape and combine them to produce a single depth map.”
Category-specific object reconstruction from a single image (2014, neutral): “However, the performance of such algorithms has only been explored on simple categories, such as SUV’s [41] or flower petal and clown fish [28].”
Single Image 3D Interpreter Network (2016, methodology): “ength, and seat width, and extrinsic properties such as its pose. In this paper, we recover these object properties from a single image by estimating 3D structure. Instead of a 3D mesh or a depth map [9,2,32,18,40,50,16], we represent an object via a 3D skeleton [47], which consists of keypoints and”
Learning 3D Object Categories by Looking Around Them (2017, methodology): “Starting from datasets of unordered images, methods such as [44] and [27] use SFM and manual annotations, such as keypoints in [4, 16], to estimate a rough 3D geometry of objects.”
Reconstructing PASCAL VOC (2014, background): “These two approaches build upon traditional non-rigid structure from motion methods [5], originally developed for reconstruction from video, and either produce sparse reconstructions [27] or have only been demonstrated on simple classes such as flower petals and clown-fish, while requiring complex m”
What Shape Are Dolphins? Building 3D Morphable Models from 2D Images (2013, unknown): “Recently, Prasad et al. [24] addressed this problem by using curve features rather than feature points, arguing that for some object classes, there are 3D curves in common across object instances.”
Learning Category-Specific Deformable 3D Models for Object Reconstruction (2017, unknown): “However, the performance of such algorithms has only been explored on simple categories, such as SUV’s [44] or flower petal and clown fish [45].”