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AI models learn to analyze and generate videos at different speeds

By PulseAugur Editorial · [4 sources] ·

Researchers have developed new methods for understanding and manipulating the flow of time in videos. One paper explores self-supervised learning to detect speed changes and estimate playback speed, enabling the creation of large slow-motion datasets and models for speed-conditioned video generation and temporal super-resolution. Another study analyzed thematic map design evolution over thirty years, using computer vision and large models to quantify map elements, color, and layout across multilingual journals, finding institutional convergence in design practices. AI

IMPACT New research explores AI's role in analyzing temporal dynamics in videos and understanding design trends in academic cartography.

RANK_REASON Two distinct academic papers are presented, one on video time manipulation and another on cartography map design evolution, both published on arXiv.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 4 sources. How we write summaries →

AI models learn to analyze and generate videos at different speeds

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Two distinct academic papers are presented, one on video time manipulation and another on cartography map design evolution, both published on arXiv.
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156 days old
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COVERAGE [4]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Seeing Fast and Slow: Learning the Flow of Time in Videos

    How can we tell whether a video has been sped up or slowed down? How can we generate videos at different speeds? Although videos have been central to modern computer vision research, little attention has been paid to perceiving and controlling the passage of time. In this paper, …

  2. arXiv cs.CV TIER_1 English(EN) · Zhiwei Wei, Chenxi Song, Tazhu Wang, Fan Wu, Hua Liao, Su Ding, Nai Yang ·

    Evolving Thematic Map Design in Academic Cartography: A Thirty-Year Study Based on Multilingual Journals

    arXiv:2604.22539v1 Announce Type: new Abstract: Thematic maps play a central role in academic communication, yet their large-scale design evolution has rarely been examined empirically. This study presents a longitudinal and multilingual analysis of thematic map design practices …

  3. arXiv cs.CV TIER_1 English(EN) · Nai Yang ·

    Evolving Thematic Map Design in Academic Cartography: A Thirty-Year Study Based on Multilingual Journals

    Thematic maps play a central role in academic communication, yet their large-scale design evolution has rarely been examined empirically. This study presents a longitudinal and multilingual analysis of thematic map design practices in academic cartography from 1990 to 2020. We co…

  4. arXiv cs.CV TIER_1 English(EN) · Wei-Chiu Ma ·

    Seeing Fast and Slow: Learning the Flow of Time in Videos

    How can we tell whether a video has been sped up or slowed down? How can we generate videos at different speeds? Although videos have been central to modern computer vision research, little attention has been paid to perceiving and controlling the passage of time. In this paper, …

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