Video generated by the current state-of-the-art generative models contain undesirable artifacts. We introduce GeneVA, the first large-scale dataset of human-annotated artifact bounding boxes in AI-generated videos. The dataset consists of 16,356 AI-generated videos, each labeled by a human annotator with per-frame artifact bounding boxes, their labels and descriptions, and video quality ratings. A custom data collection pipeline was developed in Prolific, and a novel taxonomy for spatio-temporal artifacts present in AI-generated videos was defined. The videos were from the VidProM [41] dataset, with text prompts from this dataset then used to generate an additional subset of videos using Sora. We trained an artifact detector and caption generator using a pre-trained image-based model, and a custom temporal fusion module. The dataset can be found at https://www.immersivecomputinglab.org/publication/geneva. We hope that datasets like GeneVA will encourage improvements in artifact detection in AI-generated video towards applications such as deepfake detection.

Fossils are crucial for understanding our natural history and the digitalization of fossils has paved the way for paleontologists to share and study them in greater detail. Yet, many fossil-dense regions, in particular low- and middle-income countries, lack the resources to digitalize their vast collections. This project reports on a collaboration between paleontologists and computer scientists to design, build, and operate a device that can be deployed in the field for digitizing a collection of thousands of fossils. We introduce PaleoScan, a user-friendly, cost-effective, high-volume scanner designed to expedite the digitization of extensive fossil collections. PaleoScan is a self-contained 3D scanning system consisting of a light and compact mirrorless camera, a microcontroller, a ChArUco calibration board, and user-controlled LEDs. Software and data processing is cloud-based, where the user interacts with the system through a web application. We deployed PaleoScan in a museum in Brazil with a world-class fossil collection. Our early results reveal its potential to revolutionize the scanning process for fossils.