Christoffer Koo Øhrstrøm
@chrisohrstrom.bsky.social
PhD student at DTU 🇩🇰 Doing research at the intersection of deep learning, event cameras/neuromorphic vision, multi-modal models, and robotics.
What if we could represent events (event cameras) in a way that preserves both asynchrony and spatial sparsity?
Exited to share our latest work where we answer this question positively.
Spiking Patches: Asynchronous, Sparse, and Efficient Tokens for Event Cameras
Paper: arxiv.org/abs/2510.26614
Exited to share our latest work where we answer this question positively.
Spiking Patches: Asynchronous, Sparse, and Efficient Tokens for Event Cameras
Paper: arxiv.org/abs/2510.26614
November 3, 2025 at 11:44 AM
What if we could represent events (event cameras) in a way that preserves both asynchrony and spatial sparsity?
Exited to share our latest work where we answer this question positively.
Spiking Patches: Asynchronous, Sparse, and Efficient Tokens for Event Cameras
Paper: arxiv.org/abs/2510.26614
Exited to share our latest work where we answer this question positively.
Spiking Patches: Asynchronous, Sparse, and Efficient Tokens for Event Cameras
Paper: arxiv.org/abs/2510.26614
Reposted by Christoffer Koo Øhrstrøm
Can Dynamic Neural Networks boost Computer Vision and Sensor Fusion?
We are very happy to share this awesome collection of papers on the topic!
We are very happy to share this awesome collection of papers on the topic!
First little project of the year: an awesome collection of papers on Dynamic Neural Networks for Computer Vision and Sensor Fusion!
Each paper comes with a brief summary and code link.
👉 github.com/DTU-PAS/awes...
Each paper comes with a brief summary and code link.
👉 github.com/DTU-PAS/awes...
GitHub - DTU-PAS/awesome-dynn-for-cv: Awesome collection of DyNN papers for Computer Vision and Sensor Fusion applications :sparkles:
Awesome collection of DyNN papers for Computer Vision and Sensor Fusion applications :sparkles: - DTU-PAS/awesome-dynn-for-cv
github.com
January 8, 2025 at 9:33 AM
Can Dynamic Neural Networks boost Computer Vision and Sensor Fusion?
We are very happy to share this awesome collection of papers on the topic!
We are very happy to share this awesome collection of papers on the topic!
Reposted by Christoffer Koo Øhrstrøm
Inventors of flow matching have released a comprehensive guide going over the math & code of flow matching!
Also covers variants like non-Euclidean & discrete flow matching.
A PyTorch library is also released with this guide!
This looks like a very good read! 🔥
arxiv: arxiv.org/abs/2412.06264
Also covers variants like non-Euclidean & discrete flow matching.
A PyTorch library is also released with this guide!
This looks like a very good read! 🔥
arxiv: arxiv.org/abs/2412.06264
December 10, 2024 at 8:35 AM
Inventors of flow matching have released a comprehensive guide going over the math & code of flow matching!
Also covers variants like non-Euclidean & discrete flow matching.
A PyTorch library is also released with this guide!
This looks like a very good read! 🔥
arxiv: arxiv.org/abs/2412.06264
Also covers variants like non-Euclidean & discrete flow matching.
A PyTorch library is also released with this guide!
This looks like a very good read! 🔥
arxiv: arxiv.org/abs/2412.06264