UnrealCV is an open source project to help computer vision researchers build virtual worlds using Unreal Engine 4 (UE4). It extends UE4 with a plugin by providing: A set of UnrealCV commands to interact with the virtual world.Communication between UE4 and an external program, such as Caffe.UnrealCV can be used in two ways. The first one is using a compiled game binary with UnrealCV embedded. This

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Are we there yet ? Did you ever want to quickly learn which paper provides the best results on standard dataset X ? Wait no more, just click below and discover the current state of the art. About where does this data come from ? Frustated by seeing too many papers omit the best performing methods, and inspired by Hao Wooi Lim’s blog, here you have a crowd sourced list of known result one some of t

Computer vision, image processing, research resources

Surveys of Various Computer Vision Topics Surveys of particular topics are scattered throughout the Computer Vision Bibliography under the appropriate topics and near the other related papers. Many of the topics in the Bibliography have a subsection devoted to general or survey articles so a good starting point for surveys is the contents page for the appropriate major topic. Current research and

The underground station where images are captured Sample images in the dataset Download Download Including raw images, features, and train/test partitions. Details The QMUL underGround Re-IDentification (GRID) dataset contains 250 pedestrian image pairs. Each pair contains two images of the same individual seen from different camera views. All images are captured from 8 disjoint camera views inst

See: Koen E. A. van de Sande, Theo Gevers and Cees G. M. Snoek, Evaluating Color Descriptors for Object and Scene Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 32 (9), pages 1582-1596, 2010. [PDF] [BibTeX] for an evaluation of color descriptors carried out using this software. The paper provides a structured overview of color invariant descriptors in the conte

Welcome Hi, there! We received quite a few requests for access to the product image dataset used in our paper on "Connecting Missing Links: Object Discovery from Sparse Observations Using 5 Million Product Images", published in the proceedings of ECCV 2012. We are excited to see what cool applications this dataset could facilitate out there. So we are in the process of collecting necessary permis

Lab Introduction IRIS computer vision lab is a unit of USC’s School of Engineering. It was founded in 1986 and has been a major center of government- and industry-sponsored research in computer vision and machine learning. The lab has been active in a number of research topics including object detection and recognition, face identification, 3-D modeling from a sequence of images, activity recognit

FaceTracker is a C/C++ API for real time generic non-rigid face alignment and tracking. Goal: Non-rigid face alignment and tracking is a common problem in computer vision. It is the front-end to many algorithms that require registration, for example face and expression recognition. However, those working on algorithms for these higher level tasks are often unfamiliar with the tools and peculiari

We take advantage of our autonomous driving platform Annieway to develop novel challenging real-world computer vision benchmarks. Our tasks of interest are: stereo, optical flow, visual odometry, 3D object detection and 3D tracking. For this purpose, we equipped a standard station wagon with two high-resolution color and grayscale video cameras. Accurate ground truth is provided by a Velodyne lase