The majority of modern single-view depth estimation methods predict relative depth and thus cannot be directly applied in many real-world scenarios, despite impressive performance in the benchmarks. Moreover, single-view approaches cannot guarantee consistency across a sequence of frames. Consistency is typically addressed with test-time optimization of discrepancy across views; however, it takes hours to process a single scene. In this paper, we present MEDeA, an efficient multi-view test-time depth adjustment method, that is an order of magnitude faster than existing test-time approaches. Given RGB frames with camera parameters, MEDeA predicts initial depth maps, adjusts them by optimizing local scaling coefficients, and outputs temporally-consistent depth maps. Contrary to test-time methods requiring normals, optical flow, or semantics estimation, MEDeA produces high-quality predictions with a depth estimation network solely. Our method sets a new state-of-the-art on TUM RGB-D, 7Scenes, and ScanNet benchmarks and successfully handles smartphone-captured data from ARKitScenes dataset.

Language models are increasingly attracting interest from writers. However, such models lack long-range semantic coherence, limiting their usefulness for longform creative writing. We address this limitation by applying language models hierarchically, in a system we call Dramatron. By building structural context via prompt chaining, Dramatron can generate coherent scripts and screenplays complete with title, characters, story beats, location descriptions, and dialogue. We illustrate Dramatron's usefulness as an interactive co-creative system with a user study of 15 theatre and film industry professionals. Participants co-wrote theatre scripts and screenplays with Dramatron and engaged in open-ended interviews. We report critical reflections both from our interviewees and from independent reviewers who watched stagings of the works to illustrate how both Dramatron and hierarchical text generation could be useful for human-machine co-creativity. Finally, we discuss the suitability of Dramatron for co-creativity, ethical considerations -- including plagiarism and bias -- and participatory models for the design and deployment of such tools.

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The question of what it meant to be human obsessed the ancient Greeks. The beloved myths of Hercules, Jason and the Argonauts, the sorceress Medea, the engineer Daedalus, the inventor-god Hephaestus, and the tragically inquisitive Pandora all raised the basic question of the boundaries between human and machine. Today, developments in biotechnology and advances in artificial intelligence (AI) bring a new urgency to questions about the implications of combining the biological and the technological. It's a discussion that we might say the ancient Greeks began. Medea, the mythic sorceress whose name means'to devise', knew many arcane arts. These included secrets of rejuvenation. To demonstrate her powers, Medea first appeared to Jason and the Argonauts as a stooped old woman, only to transform herself into a beautiful young princess. Jason fell under her spell and became her lover. He asked Medea to restore the youthful vigour of his aged father, Aeson.