Ood Cv

OOD-CV (Out-of-Distribution Computer Vision) research focuses on improving the robustness of computer vision algorithms against real-world variations, such as changes in object pose, shape, texture, context, and weather conditions. Current research emphasizes developing benchmark datasets and evaluating the performance of various models, including convolutional and transformer architectures, under these out-of-distribution scenarios, with a focus on techniques like domain generalization and adaptation. This work is crucial for advancing the reliability and applicability of computer vision systems in diverse and unpredictable environments, impacting fields ranging from autonomous driving to medical image analysis.