3-D Object Retrieval and Recognition With Hypergraph Analysis

By Yue Gao, Meng Wang, Dacheng Tao, Rongrong Ji, Qionghai Dai. IEEE Transactions on Image Processing, 2012

627 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/59f784eed1ff5f13aa7d3c52aba7a2af914caf6c

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In Computer Vision and Pattern Recognition

Citations in the corpus

A Bi-Directional Message Passing Model for Salient Object Detection (2018, methodology): “It can be taken as a pre-processing step in many computer vision tasks, such as scene classification [25], visual tracking [3, 21], person re-identification [40] and image retrieval [5].”
Deeply Supervised Salient Object Detection with Short Connections (2016, background): “Such a useful property allows salient object detection to commonly serve as the first step to a variety of computer vision applications including image and video compression [2], [3], image segmentation [4], content-aware image editing [5], [6], object recognition [7], weakly supervsied segmantic se”
SalientShape: group saliency in image collections (2013, background): “Determining characteristic or salient regions of images allows transitioning from low-level pixels to more meaningful high-level regions, and thus form an essential step for many computer graphics and computer vision applications, including interactive image editing [14, 16, 41, 51, 53], image retri”
Local structure preserving discriminative projections for RGB-D sensor-based scene classification (2015, background): “Introduction Scene classification has received considerable attention over the past few decades because of its wide applicability in human–computer interaction applications, such as mobile robots [29,49], smart TVs [9,10], and content-based image retrieval [8,15].”
Feature learning based on SAE-PCA network for human gesture recognition in RGBD images (2015, background): “Fortunately, along with the advent of Microsoft Kinect sensors, state-of-the-art vision-based recognition paradigms are revolted by incorporating depth cues [2], thanks to its capability to integrate information of object size, shape, and absolute position to the camera.”
Efficient Salient Region Detection with Soft Image Abstraction (2013, background): “Rather than focusing on predicting human fixation points [6, 32] (another major research direction of visual attention modeling), salient region detection methods aim at uniformly highlighting entire salient object regions, thus benefiting a large number of applications, including objectof-interest ”
Block-Row Sparse Multiview Multilabel Learning for Image Classification (2016, background): “For example, the global feature HSV has been shown less robust to the changes in frame rate, video length, and captions, while the local feature SIFT is robust to them but sensitive to changes in contrast, brightness, scale, rotation, and camera viewpoint [18]–[22].”
Pyramid Feature Attention Network for Saliency Detection (2019, background): “As the pre-processing of computer vision applications, e.g. object detection[8, 35], visual tracking[1, 14], image retrieval[10, 13] and semantic segmentation[9], saliency detection at-tracts many researchers.”
Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection (2019, background): “…including video/image segmentation [17, 40], object recognition [46], visual tracking [ 3], foreground maps evaluation [14, 15], image retrieval [6,16,22,38], content-aware image editing [8], information discovery [58], photo synthesis [5, 29], and weakly supervised semantic segmentation [52].”
A Three-Layered Graph-Based Learning Approach for Remote Sensing Image Retrieval (2016, methodology): “In another contribution [31], a probabilistic method was used to match multiple views in object retrieval.”
Hypergraph Neural Networks (2018, methodology): “Regarding the multi-modal data, in (Gao et al. 2012), multi-hypergraph structure is introduced to assign weights for different sub-hypergraphs, which corresponds to different modalities.”
Clique-graph matching by preserving global & local structure (2015, background): “On the other hand, it is mathematically difficult to impose the mapping constraints on the objective function to induce the stable solution.”