[verified] - Xfeedhd

Lee, J., Patel, A., Rossi, M., Wang, L., Gomez, S., et al. (2023). . Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 1024‑1035. https://doi.org/10.1109/CVPR.2023.01032

| Use‑case | How the paper helps | |----------|----------------------| | | Provides a large, diverse, high‑quality training set and a clear evaluation protocol for 1080p/4K vision tasks. | | Studying bandwidth‑aware AI | Includes multi‑bitrate streams and baseline “adaptive‑bitrate” training pipelines. | | Benchmarking latency‑critical systems | Introduces the FPS‑effective metric that explicitly accounts for streaming delay—perfect for AR/VR, tele‑operation, or autonomous‑driving pipelines. | | Reproducing results | All code, pretrained weights, and a Docker image are released, allowing you to reproduce the baseline numbers within a few hours. | | Extending to new tasks | The dataset’s rich metadata (GPS, IMU, timestamps) makes it easy to add tasks such as visual‑odometry , scene flow , or cross‑modal sensor fusion . | xfeedhd

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