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The objective of this track is to evaluate the performance of 3D shape retrieval approaches on a large-sale comprehensive 3D shape database that contains different types of models, such as generic, articulated, CAD and architecture models. The track is based on a new comprehensive 3D shape benchmark, which contains 8,987 triangle meshes that are classified(More)
Sketch-based 3D model retrieval is very important for applications such as 3D modeling and recognition. In this paper, a sketch-based retrieval algorithm is proposed based on a 3D model feature named View Context and 2D relative shape context matching. To enhance the accuracy of 2D sketch-3D model correspondence as well as the retrieval performance, we(More)
This paper proposes a non-photorealistic rendering method that creates an artistic effect called mosaicing. The proposed method converts images provided by the user into the mosaic images. Commercial image editing applications also provide a similar function. However, these applications often trade results for low-cost computing. It is desirable to create(More)
Sketch-based 3D shape retrieval has become an important research topic in content-based 3D object retrieval. The aim of this track is to measure and compare the performance of sketch-based 3D shape retrieval methods based on a large scale hand-drawn sketch query dataset which has 7200 sketches and a generic 3D model target dataset containing 1258 3D models.(More)
We have created a new benchmarking dataset for testing non-rigid 3D shape retrieval algorithms, one that is much more challenging than existing datasets. Our dataset features exclusively human models, in a variety of body shapes and poses. 3D models of humans are commonly used within computer graphics and vision, and so the ability to distinguish between(More)
Searching for relevant 3D models based on hand-drawn sketches is both intuitive and important for many applications , such as sketch-based 3D modeling and recognition. We propose a sketch-based 3D model retrieval algorithm by utilizing viewpoint entropy-based adaptive view clustering and shape context matching. Different models have different visual(More)
Large-scale 3D shape retrieval has become an important research direction in content-based 3D shape retrieval. To promote this research area, two Shape Retrieval Contest (SHREC) tracks on large scale comprehensive and sketch-based 3D model retrieval have been organized by us in 2014. Both tracks were based on a unified large-scale benchmark that supports(More)
A number of Non-Photorealistic Rendering methods for producing artistic style images have been developed. Recently , a method called " Image Analogies " was proposed. This method is based on the idea of example-based filtering that uses a pair of images (an original image and a filtered image) as training data and creates an image which has a style that(More)
Generic 3D shape retrieval is a fundamental research area in the field of content-based 3D model retrieval. The aim of this track is to measure and compare the performance of generic 3D shape retrieval methods implemented by different participants over the world. The track is based on a new generic 3D shape benchmark, which contains 1200 triangle meshes(More)