UCF101 dataset is an extension of UCF50 and consists of 13,320 video clips, which are classified into 101 categories. These 101 categories can be classified into 5 types (Body motion, Human-human interactions, Human-object interactions, Playing musical instruments and Sports). The total length of these video clips is over 27 hours. All the videos are collected from YouTube and have a fixed frame rate of 25 FPS with the resolution of 320 × 240.
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The Densely Annotation Video Segmentation dataset (DAVIS) is a high quality and high resolution densely annotated video segmentation dataset under two resolutions, 480p and 1080p. There are 50 video sequences with 3455 densely annotated frames in pixel level. 30 videos with 2079 frames are for training and 20 videos with 1376 frames are for validation.
634 PAPERS • 13 BENCHMARKS
The GoPro dataset for deblurring consists of 3,214 blurred images with the size of 1,280×720 that are divided into 2,103 training images and 1,111 test images. The dataset consists of pairs of a realistic blurry image and the corresponding ground truth shapr image that are obtained by a high-speed camera.
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The Middlebury Stereo dataset consists of high-resolution stereo sequences with complex geometry and pixel-accurate ground-truth disparity data. The ground-truth disparities are acquired using a novel technique that employs structured lighting and does not require the calibration of the light projectors.
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The Vimeo-90K is a large-scale high-quality video dataset for lower-level video processing. It proposes three different video processing tasks: frame interpolation, video denoising/deblocking, and video super-resolution.
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Dataset of high-resolution (4096×2160), high-fps (1000fps) video frames with extreme motion. X-TEST consists of 15 video clips with 33-length of 4K-1000fps frames. X-TRAIN consists of 4,408 clips from various types of 110 scenes. The clips are 65-length of 1000fps frames
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This is a dataset for video frame interpolation task. The dataset contains the 1920×1080 videos in 240 FPS for videos captured with iPhone 11 and in 120 FPS for gaming content captured with OBS.
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A video dataset for benchmarking upsampling methods. Inter4K contains 1,000 ultra-high resolution videos with 60 frames per second (fps) from online resources. The dataset provides standardized video resolutions at ultra-high definition (UHD/4K), quad-high definition (QHD/2K), full-high definition (FHD/1080p), (standard) high definition (HD/720p), one quarter of full HD (qHD/520p) and one ninth of a full HD (nHD/360p). We use frame rates of 60, 50, 30, 24 and 15 fps for each resolution. Based on this standardization, both super-resolution and frame interpolation tests can be performed for different scaling sizes ($\times 2$, $\times 3$ and $\times 4$). In this paper, we use Inter4K to address frame upsampling and interpolation. Inter4K provides both standardized UHD resolution and 60 fps for all of videos by also containing a diverse set of 1,000 5-second videos. Differences between scenes originate from the equipment (e.g., professional 4K cameras or phones), lighting conditions, vari
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SlowFlow is an optical flow dataset collected by applying Slow Flow technique on data from a high-speed camera and analyzing the performance of the state-of-the-art in optical flow under various levels of motion blur.
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ATD-12K is a large-scale animation triplet dataset, which comprises 12,000 triplets(train10k,test2k) by manually inspect and the test2k with rich annotations, including levels of difficulty, the Regions of Interest (RoIs) on movements, and tags on motion categories
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To test interpolation performance on various texture types, we developed a new test set, VFITex, which contains twenty 100-frame UHD or HD videos at 24, 30 or 50 FPS, collected from the Xiph, Mitch Martinez Free 4K Stock Footage, UVG database and pexels.com. This dataset covers diverse textured scenes, including crowds, flags, foliage, animals, water, leaves, fire and smoke. HD patches were center-cropped from the UHD sequences, preserving the original UHD characteristics. All frames in each sequence were used for evaluation, totaling 940 quintuplets.
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SEPE 8K dataset is made of 40 different 8K (8192 x 4320) video sequences and 40 variant 8K (8192 x 5464) images. The video sequences were captured at a framerate of 29.97 frames per second (FPS) and had been encoded into videos using AVC/H.264, HEVC/H.265, and AV1 codecs at resolutions from 8K to 480p. The images, video sequences, encoded videos, and various other statistics related to the media that make the dataset are stored online, published, and maintained on the repo on GitHub for non-commercial use. this proposed dataset is - as far as we know - the first to publish true 8K natural sequences; thus, it is important for the next level of applications dealing with multimedia such as video quality assessment, super-resolution, video coding, video compression, and many more.
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