mlsanityData to 7 Oct 2026

Actions ~ Transformations

arXiv 1512.00795 ↗First posted 2 Dec 2015cs.CVcited by 30

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Abstract (arXiv)

What defines an action like "kicking ball"? We argue that the true meaning of an action lies in the change or transformation an action brings to the environment. In this paper, we propose a novel representation for actions by modeling an action as a transformation which changes the state of the environment before the action happens (precondition) to the state after the action (effect). Motivated by recent advancements of video representation using deep learning, we design a Siamese network which models the action as a transformation on a high-level feature space. We show that our model gives improvements on standard action recognition datasets including UCF101 and HMDB51. More importantly, our approach is able to generalize beyond learned action categories and shows significant performance improvement on cross-category generalization on our new ACT dataset.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Dec 2015.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 10; 2023: 5; 2024: 6; 2025: 2; 2026: 2.

30 papers.

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  1. 2021Ego4D: Around the World in 3,000 Hours of Egocentric Videocited by 1,530
  2. 2024STAR: A Benchmark for Situated Reasoning in Real-World Videoscited by 213
  3. 2022EgoTaskQA: Understanding Human Tasks in Egocentric Videoscited by 112
  4. 2021PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D Worldcited by 47
  5. 2021With a Little Help from my Temporal Context: Multimodal Egocentric Action Recognitioncited by 41
  6. 2023Vamos: Versatile Action Models for Video Understandingcited by 40
  7. 2022Look for the Change: Learning Object States and State-Modifying Actions from Untrimmed Web Videoscited by 39
  8. 2022Understanding 3D Object Articulation in Internet Videoscited by 36
  9. 2023Learning Object State Changes in Videos: An Open-World Perspectivecited by 36
  10. 2022Deep Unsupervised Key Frame Extraction for Efficient Video Classificationcited by 14
  11. 2024Self-supervised visual learning from interactions with objectscited by 10
  12. 2023Action Dynamics Task Graphs for Learning Plannable Representations of Procedural Taskscited by 8
18 more
  1. 2024Rethinking Image-to-Video Adaptation: An Object-centric Perspectivecited by 8
  2. 2022Noise-Tolerant Learning for Audio-Visual Action Recognitioncited by 7
  3. 2021Detecting Object States vs Detecting Objects: A New Dataset and a Quantitative Experimental Studycited by 6
  4. 2022Video-based Human Action Recognition using Deep Learning: A Reviewcited by 6
  5. 2025What Changed and What Could Have Changed? State-Change Counterfactuals for Procedure-Aware Video Representation Learningcited by 6
  6. 2022Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequencescited by 5
  7. 2024Learning to Visually Connect Actions and their Effectscited by 2
  8. 2024Anticipating Object State Changes in Long Procedural Videoscited by 2
  9. 2024A Survey of Recent Advances and Challenges in Deep Audio-Visual Correlation Learningcited by 2
  10. 2022Human Activity Recognition Using Cascaded Dual Attention CNN and Bi-Directional GRU Frameworkcited by 1
  11. 2022FuTH-Net: Fusing Temporal Relations and Holistic Features for Aerial Video Classificationcited by 1
  12. 2023Recognizing Unseen States of Unknown Objects by Leveraging Knowledge Graphscited by 1
  13. 2026TeCoNeRV: Leveraging Temporal Coherence for Compressible Neural Representations for Videoscited by 1
  14. 2021Precondition and Effect Reasoning for Action Recognitioncited by 0
  15. 2022Recent Advances and Challenges in Deep Audio-Visual Correlation Learningcited by 0
  16. 2023Visual Reasoning: from State to Transformationcited by 0
  17. 2025Vision-Based Mistake Analysis in Procedural Activities: A Review of Advances and Challengescited by 0
  18. 2026UniMPA: A Unified Memory-Prediction-Action Model via Action-Grounded Transition Modelingcited by 0