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Objectives: Provide a set of stereo vision benchmarks. Outcomes: Influenced the development of algorithms that effectively process stereo image pairs to recover depth information.

Objectives: Provide image recognition, segmentation, and captioning benchmarks. Outcomes: Establishment of a large-scale dataset that facilitates algorithm development for image understanding.

Objectives: Advance research in artificial intelligence and robotics, focused on soccer-playing robots. Outcomes: Development of collaborative and autonomous robotic technologies.

Objectives: Evaluate algorithms for object detection and image classification at large scale. Outcomes: Advancement of deep learning techniques, notably convolutional neural networks (CNNs).

Objectives: Contribute to computer vision algorithms applied to autonomous driving. Outcomes: A valuable dataset for mobile robotics and autonomous driving research with emphasis on vision-based tasks.

Objectives: Accelerate the development of autonomous ground vehicles. Outcomes: Paving the way for advances in self-driving car technology.

Objectives: Provide a dataset and benchmarks that focus on semantic understanding of urban street scenes. Outcomes: Development of new algorithms that can handle complex urban scene understanding for autonomous vehicles.