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Multi-model fitting aims to robustly estimate the parameters of various model instances in data contaminated by noise and outliers. Most previous works employ only a single type of consensus or implicit fusion model to represent the correlation between ...

Motions in videos are typically a mixture of local dynamic object motions and global camera motion, which are inconsistent in some cases, and even interfere with each other, causing difficulties in various downstream applications, such as video ...

• A unified framework to estimate global and local motion simultaneously.
• An implicit–explicit bottleneck for global motion without irrelevant information.
• Two loss functions to learn global and local motion in a self-supervised ...

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More than 80% of video coding times are consumed by motion estimation calculations, which are the most complex aspect of the process. This method eliminates temporal redundancies in a video sequence to achieve maximum compression. Numerous efforts have ...

To reduce the amount of unnecessary data in a video's timeline, block-based motion estimate is routinely utilised. However, a significant reduction in the computational complexity of motion estimation remains a significant problem. In this manuscript, a ...

Recently, online optimisation‐based scene flow estimation has attracted significant attention due to its strong domain adaptivity. Although online optimisation‐based methods have made significant advances, the performance is far from ...

The authors introduce a dual‐branch MLP‐based architecture to encode implicit scene representations from a source 3D point cloud, which can additionally synthesise a target 3D point cloud. Thus, the mapping function between the source and synthesised ...

As one of the underlying tasks of computer vision, image and video reconstruction have an extensive research value. Video is interpreted as a sequence of images arranged based on a timeline. The spatio-temporal correlation leads to adjacent sequences ...

Inspired by biological vision mechanism, event‐based cameras have been developed to capture continuous object motion and detect brightness changes independently and asynchronously, which overcome the limitations of traditional frame‐based cameras. ...

As event camera outputs are sparse and uneven, dense scene information is difficult to generate and the local receptive fields of the neural network also lead to poor moving objects tracking. To address these issues, we propose an improved event‐based ...

From a 2D video of a person in action, human mesh recovery aims to infer the 3D human pose and shape frame by frame. Despite progress on video‐based human pose and shape estimation, it is still challenging to guarantee high accuracy and smoothness ...

From a video of a person in action, human mesh recovery aims to infer the 3D human pose and shape. We propose a Video2mesh, a temporal convolutional transformer (TConvTransformer) network which is able to recover accurate and smooth human mesh from 2D ...

Precipitation forecasting plays an important role in disaster warning, agricultural production, and other fields. To solve this issue, some deep learning methods are proposed to forecast future radar echo images and convert them into rainfall ...

• Non-invasive characterization of bladder dynamics during deep respiratory movements from dynamic Magnetic Resonance Imaging.

Background and objectives: Dynamic Magnetic Resonance Imaging (MRI) may capture temporal anatomical changes in soft tissue organs with high-contrast but the obtained sequences usually suffer from limited volume coverage ...

This paper proposes a fast partial distortion-based block matching motion estimation algorithm in Walsh–Hadamard. The proposed algorithm divides the current block into subblocks and provides a sequence of fine-partial distortions to reject the ...

Several video coding standards and techniques have been introduced for multimedia applications, particularly h.26x series for video processing. These standards employ motion estimation process for reducing the amount of data that is required to ...

Digital video stabilization is a challenging task that aims to transform a potentially shaky video into a pleasant one by smoothing the camera trajectory. Despite the various works found in the literature addressing this task, their organization and ...

The size of video data is growing exponentially worldwide and hence there is a need for better video coding standards. MPEG and H.26X have provided several standards for video coding. The latest and effective video coding standards are AVC, HEVC, and AV1. ...

The demand for creating rendered content continues to drastically grow. As it often is extremely computationally expensive and thus costly to render high-quality computer-generated images, there is a high incentive to reduce this computational burden. ...

In this work, we study the problem of separating the global camera motion and the local dynamic motion from an optical flow. Previous methods either estimate global motions by a parametric model, such as a homography, or estimate both of them by an ...

Small unmanned aerial vehicles (UAVs) have developed rapidly and are widely used for disaster relief, traffic monitoring and military surveillance. To perform these tasks better, it is necessary to improve the environmental perception ability of ...

The information present in the footage/video clip is one of the solid evidence of the event at the incidents. Therefore, visual media crime-scene investigation has risen as a crucial research field, which fundamentally promotes techniques to deal with ...

In this paper, a novel compression framework based on 3D point cloud data is proposed for telepresence, which consists of two parts. One is implemented to remove the spatial redundancy, i.e., a robust Bayesian framework is designed to track the ...

Human motion prediction is an important and challenging task in computer vision with various applications. Recurrent neural networks (RNNs) and convolutional neural networks (CNNs) have been proposed to address this challenging task. However, RNNs ...