FANVID: A Benchmark for Face and License Plate Recognition in Low-Resolution Videos

Real-world surveillance often renders faces and license plates unrecognizable in individual low-resolution (LR) frames, hindering reliable identification. To advance temporal recognition models, we present FANVID, a novel video-based benchmark comprising nearly 1,463 LR clips (180 x 320, 20--60 FPS) featuring 63 identities and 49 license plates from three English-speaking countries. Each video includes distractor faces and plates, increasing task difficulty and realism. The dataset contains 31,096 manually verified bounding boxes and labels. FANVID defines two tasks: (1) face matching -- detecting LR faces and matching them to high-resolution mugshots, and (2) license plate recognition -- extracting text from LR plates without a predefined database. Videos are downsampled from high-resolution sources to ensure that faces and text are indecipherable in single frames, requiring models to exploit temporal information. We introduce evaluation metrics adapted from mean Average Precision at IoU > 0.5, prioritizing identity correctness for faces and character-level accuracy for text. A baseline method with pre-trained video super-resolution, detection, and recognition achieved performance scores of 0.58 (face matching) and 0.42 (plate recognition), highlighting both the feasibility and challenge of the tasks. FANVID's selection of faces and plates balances diversity with recognition challenge. We release the software for data access, evaluation, baseline, and annotation to support reproducibility and extension. FANVID aims to catalyze innovation in temporal modeling for LR recognition, with applications in surveillance, forensics, and autonomous vehicles.

Towards ubiquitous radio access using nanodiamond based quantum receivers

The development of sixth-generation (6G) wireless communication systems demands innovative solutions to address challenges in the deployment of a large number of base stations and the detection of multi-band signals. Quantum technology, specifically nitrogen vacancy (NV) centers in diamonds, offers promising potential for the development of compact, robust receivers capable of supporting multiple users. For the first time, we propose a multiple access scheme using fluorescent nanodiamonds (FNDs) containing NV centers as nano-antennas. The unique response of each FND to applied microwaves allows for distinguishable patterns of fluorescence intensities, enabling multi-user signal demodulation. We demonstrate the effectiveness of our FNDs-implemented receiver by simultaneously transmitting two uncoded digitally modulated information bit streams from two separate transmitters, achieving a low bit error ratio. Moreover, our design supports tunable frequency band communication and reference-free signal decoupling, reducing communication overhead. Furthermore, we implement a miniaturized device comprising all essential components, highlighting its practicality as a receiver serving multiple users simultaneously. This approach paves the way for the integration of quantum sensing technologies in future 6G wireless communication networks.