Recurrent Temporal Deep Field for Semantic Video Labeling—Supplementary Material
نویسندگان
چکیده
1 Derivation of Mean-field Updating Equations In the following we present a detailed derivation of the mean-field inference algorithm which is explained in Sec. 4 in [2] (i.e., Inference of RTDF). Here, we use the same notation as in [2]. The Kullback-Leibler divergence betweenQ(y,h;μ,ν) and P (y,h|y, I) is defined as KL(Q||P ) = ∑ yt,ht Q(y,h;μ,ν) ln Q(y,h;μ,ν) P (yt,ht|y<t, It) = −H(Q)− ∑ yt,ht Q(y,h;μ,ν) lnP (y,h|y, I) (1)
منابع مشابه
Recurrent Temporal Deep Field for Semantic Video Labeling
This paper specifies a new deep architecture, called Recurrent Temporal Deep Field (RTDF), for semantic video labeling. RTDF is a conditional random field (CRF) that combines a deconvolution neural network (DeconvNet) and a recurrent temporal restricted Boltzmann machine (RTRBM). DeconvNet is grounded onto pixels of a new frame for estimating the unary potential of the CRF. RTRBM estimates a hi...
متن کاملSemantic Video Segmentation by Gated Recurrent Flow Propagation
Semantic video segmentation is challenging due to the sheer amount of data that needs to be processed and labeled in order to construct accurate models. In this paper we present a deep, end-to-end trainable methodology to video segmentation that is capable of leveraging information present in unlabeled data in order to improve semantic estimates. Our model combines a convolutional architecture ...
متن کاملRecognition of Visual Events using Spatio-Temporal Information of the Video Signal
Recognition of visual events as a video analysis task has become popular in machine learning community. While the traditional approaches for detection of video events have been used for a long time, the recently evolved deep learning based methods have revolutionized this area. They have enabled event recognition systems to achieve detection rates which were not reachable by traditional approac...
متن کاملReading the Videos: Temporal Labeling for Crowdsourced Time-Sync Videos Based on Semantic Embedding
Recent years have witnessed the boom of online sharing media contents, which raise significant challenges in effective management and retrieval. Though a large amount of efforts have been made, precise retrieval on video shots with certain topics has been largely ignored. At the same time, due to the popularity of novel time-sync comments, or so-called “bullet-screen comments”, video semantics ...
متن کاملImproving Semantic Video Segmentation by Dynamic Scene Integration
Multi-class image segmentation and pixel-level labeling of the frames that make up a video could be made more efficient by incorporating temporal information. Recently, Convolutional Neural Networks (ConvNets) have made an impressive positive impact on the single image segmentation problem. In this paper, in order to further increase labeling accuracy, we propose a method for integrating short-...
متن کامل