Layered segmentation and optical flow estimation over time

By Deqing Sun, Erik B. Sudderth, Michael J. Black. 2012

146 citations recorded by the source corpus.

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Citations in the corpus

Optical Flow with Semantic Segmentation and Localized Layers (2016, methodology): “Also, while the depth order of layers is important, this may be ambiguous in two frames [48].”
Layered RGBD scene flow estimation (2015, background): “Recent RGB layered methods [40, 41] have obtained promising results in the presence of occlusions, but are computationally expensive.”
NeuMan: Neural Human Radiance Field from a Single Video (2022, methodology): “The scene NeRF model is analogous to the background model in traditional motion detection work [41,6,16], except it’s a NeRF.”
A Fully-Connected Layered Model of Foreground and Background Flow (2013, methodology): “Layered models [8, 12, 30] are promising for motion analysis, particularly for handling occlusion and capturing temporally consistent scene structure [27].”
Optical flow modeling and computation: A survey (2015, methodology): “The related layered approach [233,234] achieving state-of-the-art results requires several hours to process a pair of 640 (cid”
A Quantitative Analysis of Current Practices in Optical Flow Estimation and the Principles Behind Them (2013, methodology): “Severalrecent and high-ranking methods directly build on Classic+NL , such as layered models (Sun et al. 2010b, 2012, 2013), meth-ods with more advanced motion prior models (Chen et al. 2012; Jia et al. 2011), efﬁcient optimization schemes for the non-local term (Krähenbühl and Koltun 2012), and…”
Video Segmentation via Object Flow (2016, background): “These models can be extended to the temporal domain with more than two frames [31].”
Efficient sparse-to-dense optical flow estimation using a learned basis and layers (2015, methodology): “Layered models [13, 23, 42, 45, 46, 49] provide another approach.”
Ieee Transactions on Pattern Analysis and Machine Intelligence Segmentation of Moving Objects by Long Term Video Analysis (2014, unknown): “While early approaches estimate the optical flow and the segmentation independently [69], [56], optical flow estimation and segmentation were later considered as a joint optimization problem [25], [3], [15], [63].”