Superpixel Convolutional Networks using Bilateral Inceptions
We introduce a new 'bilateral inception' module that can be inserted in existing CNN architectures and performs bilateral filtering, at multiple feature-scales, between superpixels in an image.
Higher Order Conditional Random Fields in Deep Neural Networks
Recent deep learning approaches have incorporated CRFs into Convolutional Neural Networks (CNNs), with some even training the CRF end-to-end with the rest of the network.
STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling
The proposed network produces a high quality segmentation of a single image by leveraging information from additional views of the same scene.
Superpixel Hierarchy
Quantitative and qualitative evaluation on a number of computer vision applications was conducted, demonstrating that the proposed method is the top performer.
Video Object Segmentation using Supervoxel-Based Gerrymandering
Focusing on the problem of strictly unsupervised video object segmentation, we devise a method called supervoxel gerrymandering that links masks of foregroundness and backgroundness via local and non-local consensus measures.
Robust Interpolation of Correspondences for Large Displacement Optical Flow
In this paper, we present a Robust Interpolation method of Correspondences (called RicFlow) to overcome the weakness.
Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes
YangZhang4065/AdaptationSeg
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ICCV 2017
Hence, we propose a curriculum-style learning approach to minimize the domain gap in urban scenery semantic segmentation.
Semantic Instance Labeling Leveraging Hierarchical Segmentation
Most of the approaches for indoor RGBD semantic la- beling focus on using pixels or superpixels to train a classi- fier.
Supervised and unsupervised segmentation using superpixels, model estimation, and Graph Cut.
Image segmentation is widely used as an initial phase of many image analysis tasks.
Region growing using superpixels with learned shape prior.
Region growing is a classical image segmentation method based on hierarchical region aggregation using local similarity rules.