Shuhan Tan
@stan188249301
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CS PhD student at UT Austin
Joined August 2019
Happy to share our latest work on efficient sensor tokenization for end-to-end driving architectures! https://t.co/nkYUIzfyJT We introduce a novel way to tokenize multi-camera input for AV Transformers that is resolution- and camera-count-agnostic, yet geometry-aware 🧵👇
arxiv.org
Autoregressive Transformers are increasingly being deployed as end-to-end robot and autonomous vehicle (AV) policy architectures, owing to their scalability and potential to leverage...
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Language Conditioned Traffic Generation paper page: https://t.co/LFzlxhNUPY Simulation forms the backbone of modern self-driving development. Simulators help develop, test, and improve driving systems without putting humans, vehicles, or their environment at risk. However,
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Dense observations with perfect camera poses are hard to collect. What is a more practical setting for large-scale general object reconstruction? Presenting FORGE - jointly recovering object shape and camera poses from few-view observations, and it generalizes to novel
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We are announcing the first AV4D: Visual Learning of Sounds in Spaces Workshop @eccvconf 2022! This workshop shares recent progress of audio-visual learning driven by emerging applications in robotics, AR, VR, etc. Now call for papers📢. See more info at https://t.co/pAVmIId94t.
av4d.org
EVisual Learning of Sounds in Spaces Workshop at ICCV 2023 (Hybrid)
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