Results 61 to 70 of about 1,483,995 (324)
BiFormer: Learning Bilateral Motion Estimation via Bilateral Transformer for 4K Video Frame Interpolation [PDF]
Computer Vision and Pattern Recognition, 2023 A novel 4K video frame interpolator based on bilateral transformer (BiFormer) is proposed in this paper, which performs three steps: global motion estimation, local motion refinement, and frame synthesis.
Jun-ho Park, Jintae Kim, Chang-Su Kim
semanticscholar +1 more source
A concealment based approach to distributed video coding [PDF]
, 2008 This paper presents a concealment based approach to distributed video coding that uses hybrid key/WZ frames via an FMO type interleaving of macroblocks. Our motivation stems from a previous work of ours that showed promising results relative to the more ...
Agrafiotis, D +2 more
core +3 more sources
Enhanced spatial error concealment with directional entropy based interpolation switching [PDF]
, 2006 This paper describes a spatial error concealment method that uses edge related information for concealing missing macroblocks in a way that not only preserves existing edges but also avoids introducing new strong ones.
Agrafiotis, D, Bull, DR, Canagarajah, CN
core +2 more sources
A Convolutional Neural Network Approach for Half-Pel Interpolation in Video Coding
, 2017 Motion compensation is a fundamental technology in video coding to remove the temporal redundancy between video frames. To further improve the coding efficiency, sub-pel motion compensation has been utilized, which requires interpolation of fractional ...
Li, Houqiang +3 more
core +1 more source
Motion-Aware Video Frame Interpolation
Neural NetworksVideo frame interpolation methodologies endeavor to create novel frames betwixt extant ones, with the intent of augmenting the video's frame frequency. However, current methods are prone to image blurring and spurious artifacts in challenging scenarios involving occlusions and discontinuous motion.
Pengfei Han +3 more
openaire +3 more sources
PhaseNet for Video Frame Interpolation [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Most approaches for video frame interpolation require accurate dense correspondences to synthesize an in-between frame. Therefore, they do not perform well in challenging scenarios with e.g. lighting changes or motion blur. Recent deep learning approaches that rely on kernels to represent motion can only alleviate these problems to some extent.
Meyer, Simone +5 more
openaire +2 more sources
Efficient Video Frame Interpolation Using Generative Adversarial Networks
Applied Sciences, 2020 Frame interpolation, which generates an intermediate frame given adjacent ones, finds various applications such as frame rate up-conversion, video compression, and video streaming.
Quang Nhat Tran, Shih-Hsuan Yang
doaj +1 more source
Error concealment using motion field interpolation [PDF]
, 1998 In the context of block-based video coding, two error concealment algorithms are presented. The first algorithm is based on bilinear motion field interpolation (BMFI). For each pel in a damaged block, the algorithm recovers a motion vector using bilinear
Al-Mualla, MES +2 more
core +2 more sources
Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network [PDF]
, 2016 Recently, several models based on deep neural networks have achieved great success in terms of both reconstruction accuracy and computational performance for single image super-resolution. In these methods, the low resolution (LR) input image is upscaled
Aitken, AP +7 more
core +2 more sources
Disambiguation for Video Frame Interpolation
, 2023 Existing video frame interpolation (VFI) methods blindly predict where each object is at a specific timestep t ("time indexing"), which struggles to predict precise object movements. Given two images of a baseball, there are infinitely many possible trajectories: accelerating or decelerating, straight or curved.
Zhong, Zhihang +7 more
openaire +2 more sources