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Joseph Gesnouin

Observed name: Gesnouin, Joseph
ORCID: 0000-0002-9519-3591
Observed ORCID: 0000-0002-9519-3591
OpenAlex ID: A5018579471
TrouSPI-Net: Spatio-temporal attention on parallel atrous convolutions and U-GRUs for skeletal pedestrian crossing prediction
2021 · Joseph Gesnouin, Steve Pechberti, et al. · International Conference on Automatic Face and Gesture Recognition · 55
Predicting Intentions of Pedestrians from 2D Skeletal Pose Sequences with a Representation-Focused Multi-Branch Deep Learning Network
2020 · Joseph Gesnouin, Steve Pechberti, et al. · Algorithms · 41
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Assessing Cross-dataset Generalization of Pedestrian Crossing Predictors
2022 · Joseph Gesnouin, Steve Pechberti, et al. · IEEE Intelligent Vehicles Symposium · 25
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LLaMandement: Large Language Models for Summarization of French Legislative Proposals
2024 · Gesnouin, Joseph, Tannier, Yannis, et al. · arXiv (Cornell University) · 19
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Asymmetrical Bi-RNN for pedestrian trajectory encoding
2021 · Rozenberg, Raphaël, Gesnouin, Joseph, et al. · arXiv (Cornell University) · 17
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GraphRAG: Leveraging Graph-Based Efficiency to Minimize Hallucinations in LLM-Driven RAG for Finance Data
2025 · Barry, Mariam, Caillaut, Gaëtan, et al. · HAL · 4
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Analysis of pedestrian movements and gestures using an on-board camera to predict their intentions
2022 · Joseph Gesnouin · theses.fr (ABES) · 4
TrouSPI-Net: Spatio-temporal attention on parallel atrous convolutions and U-GRUs for skeletal pedestrian crossing prediction
2021 · Gesnouin, Joseph, Pechberti, Steve, et al. · arXiv (Cornell University) · 2
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LLaMandement: Large Language Models for Summarization of French Legislative Proposals
2025 · Gesnouin, Joseph, Tannier, Yannis, et al. · HAL
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Asymmetrical Bi-RNNs, 3rd place solution at the ICCV Trajnet++ Challenge
2021 · Rozenberg, Raphaël, Gesnouin, Joseph, et al. · HAL
Asymmetrical Bi-RNNs (U-RNNs), 2nd place solution at the Trajnet++ Challenge for pedestrian trajectory forecasting
2021 · Rozenberg, Raphaël, Gesnouin, Joseph, et al. · HAL
Works count: 11
Citation count: 167
H-index: 5
I10-index: 5
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