Human-AI Divergence in Ego-centric Action Recognition under Spatial and Spatiotemporal Manipulations

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References (80)

[1]
Seeing Just Enough: The Contribution of Hands, Objects and Visual Features to Egocentric Action Recognition
2026Filip Rybansky, Sadegh Rahmaniboldaji et al.
[2]
Human vs. Machine Minds: Ego-Centric Action Recognition Compared
2025Sadegh Rahmani-Boldaji, Filip Rybansky et al.
[3]
VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding
2025Boqiang Zhang, Kehan Li et al.
[4]
DEAR: Depth-Enhanced Action Recognition
2024Sadegh Rahmaniboldaji, Filip Rybansky et al.
[5]
SAM 2: Segment Anything in Images and Videos
2024Nikhila Ravi, Valentin Gabeur et al.
[6]
FILS: Self-Supervised Video Feature Prediction In Semantic Language Space
2024Mona Ahmadian, F. Guerin et al.
[7]
Side4Video: Spatial-Temporal Side Network for Memory-Efficient Image-to-Video Transfer Learning
2023Huanjin Yao, Wenhao Wu et al.
[8]
MOFO: MOtion FOcused Self-Supervision for Video Understanding
2023Mona Ahmadian, Frank Guerin et al.
[9]
Do humans and Convolutional Neural Networks attend to similar areas during scene classification: Effects of task and image type
2023Romy Müller, Marcel Duerschmidt et al.
[10]
Deep problems with neural network models of human vision
2022J. Bowers, Gaurav Malhotra et al.
[11]
Harmonizing the object recognition strategies of deep neural networks with humans
2022Thomas Fel, Ivan Felipe et al.
[12]
ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints
2022Yinpeng Dong, Shouwei Ruan et al.
[13]
If a Human Can See It, So Should Your System: Reliability Requirements for Machine Vision Components
2022Boyue Caroline Hu, Lina Marsso et al.
[14]
Noise-trained deep neural networks effectively predict human vision and its neural responses to challenging images
2021Hojin Jang, Devin McCormack et al.
[15]
Feature blindness: A challenge for understanding and modelling visual object recognition
2021Gaurav Malhotra, M. Dujmović et al.
[16]
Oculo-retinal dynamics can explain the perception of minimal recognizable configurations
2021L. Gruber, S. Ullman et al.
[17]
Partial success in closing the gap between human and machine vision
2021Robert Geirhos, Kantharaju Narayanappa et al.
[18]
Qualitative similarities and differences in visual object representations between brains and deep networks
2021Georgin Jacob, R. Pramod et al.
[19]
From Observed Action Identity to Social Affordances.
2021G. Orban, M. Lanzilotto et al.
[20]
Learning Transferable Visual Models From Natural Language Supervision
2021Alec Radford, Jong Wook Kim et al.

Showing 20 of 80 references

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"Identify and leverage minimal visual cues for robust action recognition, bridging the gap between human and AI performance in real-world scenarios."

Action RecognitionScore: 7View PDF ↗

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5

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7.5

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5

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