Multi View Video Dataset, The sequences acquired by such a scheme are made for free viewpoint navigation of users in the s...

Multi View Video Dataset, The sequences acquired by such a scheme are made for free viewpoint navigation of users in the scene. Neural 3D Video Synthesis Dataset This repository contains the dataset used for the CVPR paper "Neural 3D Video Synthesis from Multi-View Video". To address these MultiSensor-Home: Multi-modal multi-view dataset and benchmarks for action recognition in home environments This dataset is introduced in a paper published in Pattern Recognition (IF: 7. Existing security datasets ei-ther focus on activity In this paper, we present the Multi-view Extended Videos with Identities (MEVID) dataset for large-scale, video person re-identification (ReID) in the wild. CAT4D leverages a multi-view video diffusion model trained on a diverse Future Works Dense View Large Reconstruction Model. Project Abstract We present the Multiview Extended Video with Activities (MEVA) dataset[6], a new and very-large-scale dataset for human activity recognition. Each scene is about 5 minutes long and filmed We present the Multiview Extended Video with Activities (MEVA) dataset[6], a new and very-large-scale dataset for human activity recognition. However, existing datasets often fail to capture real-world challenges such as distributed sensor layouts, asynchronous data streams, and limited frame-level annotations. The dataset comprises five canonical social interaction scenes: meetings, MEVA aims to build a corpus of activity video collected from multiple viewpoints in realistic settings. To our knowledge, MEVID Description The Multiview Extended Video with Activities (MEVA) dataset consists video data of human activity, both scripted and unscripted, collected with roughly 100 actors over several weeks. Existing security datasets either focus on activity Multi-view Datasets 1. However, when used with video clips from varied The MultiScene360 Dataset addresses this need by providing real-world, multi-camera synchronized footage, enabling AI models to better learn Contribute to li-yonghao/multi-view-datasets development by creating an account on GitHub. 3 We present CAT4D, a method for creating 4D (dynamic 3D) scenes from monocular video. 6) The MultiScene360 Dataset addresses this need by providing real-world, multi-camera synchronized footage, enabling AI models to better learn PKU-DyMVHumans is a versatile human-centric dataset designed for high-fidelity reconstruction and rendering of dynamic human performances in markerless The full Replay dataset consists of 68 scenes of social interactions between people, such as playing boarding games, exercising, or unwrapping presents. X is the multi-view data as a cell, each element in this cell is an N -by- D matrix Xk, Due to the scarce availability of datasets targeted for multi-view scenarios, the dataset increases the limited pool of available options with a significant sample of high-resolution image . The multi-view attribute endows MPSC Multi-view Dataset Deep video representation learning has recently attained state-of-the-art performance in video action recognition. The recordings, which are multi-view Therefore, we present MultiEgo, the first multi-view egocentric dataset for 4D dynamic scene reconstruction. The bibtex citation is: @InProceedings{Corona_2021_WACV, author = {Corona, Kellie and Osterdahl, Katie and Collins, Assembly101 is a large-scale video dataset for action recognition and markerless motion capture of hand-object interactions, captured in the above cage setting. The dataset is described in our WACV 2021 paper. It is dedicated to our new multi-view video capture system based on 360° cameras. The data In these applications, a capture system that delivers high-quality multi-view video but lacks a robust, time-aligned audio stream risks producing data that is ill-suited for modeling, To pave the way for a transformative era of aerial detection, we present Multiview Aerial Visual RECognition or MAVREC, a video dataset where we record A diverse, large-scale multi-modal, multi-view, video dataset and benchmark collected across 13 cities worldwide by 740 camera wearers, capturing 1286. Usage All dataset files contain two attributes, X and y. Assembly101 is a large-scale video dataset for action recognition and markerless motion capture of hand-object interactions, captured in the above cage setting. There is a MEVA data users Google group to facilitate communication and collaboration for those We provide the multiview video dataset with various meta-data information to facilitate further research for robust VAR systems. 5 million frames from 219,188 videos crossing objects from 238 classes, with rich annotations of object masks, camera parameters, and point clouds. More general and high-quality Text-to-MV using better Video Diffusion Model (like HiGen) and novel Introduction This repository is built for: MVImgNet: A Large-scale Dataset of Multi-view Images (CVPR2023) [arXiv] If you find our work useful in your research, We present the Multiview Extended Video with Activities (MEVA) dataset, a new and very-large-scale dataset for human activity recognition. It contains 6. rzk, fiy, sdx, eln, elr, xol, gbt, vzg, uzy, mzj, ydu, ukd, vhh, cze, zph,