Talking Papers Podcast
🎙️ Welcome to the Talking Papers Podcast: Where Research Meets Conversation 🌟
Are you ready to explore the fascinating world of cutting-edge research in computer vision, machine learning, artificial intelligence, graphics, and beyond? Join us on this podcast by researchers, for researchers, as we venture into the heart of groundbreaking academic papers.
At Talking Papers, we've reimagined the way research is shared. In each episode, we engage in insightful discussions with the main authors of academic papers, offering you a unique opportunity to dive deep into the minds behind the innovation.
📚 Structure That Resembles a Paper 📝
Just like a well-structured research paper, each episode takes you on a journey through the academic landscape. We provide a concise TL;DR (abstract) to set the stage, followed by a thorough exploration of related work, approach, results, conclusions, and a peek into future work.
🔍 Peer Review Unveiled: "What Did Reviewer 2 Say?" 📢
But that's not all! We bring you an exclusive bonus section where authors candidly share their experiences in the peer review process. Discover the insights, challenges, and triumphs behind the scenes of academic publishing.
🚀 Join the Conversation 💬
Whether you're a seasoned researcher or an enthusiast eager to explore the frontiers of knowledge, Talking Papers Podcast is your gateway to in-depth, engaging discussions with the experts shaping the future of technology and science.
🎧 Tune In and Stay Informed 🌐
Don't miss out on the latest in research and innovation.
Subscribe and stay tuned for our enlightening episodes. Welcome to the future of research dissemination – welcome to Talking Papers Podcast!
Enjoy the journey! 🌠
#TalkingPapersPodcast #ResearchDissemination #AcademicInsights
Talking Papers Podcast
Cameras as Rays - Jason Y. Zhang
Talking Papers Podcast Episode: "Cameras as Rays: Pose Estimation via Ray Diffusion" with Jason Zhang
Welcome to the latest episode of the Talking Papers Podcast! This week's guest is Jason Zhang, a PhD student at the Robotics Institute at Carnegie Mellon University who joined us to discuss his paper, "Cameras as Rays: Pose Estimation via Ray Diffusion". The paper was published in the highly-respected conference ICLR, 2024.
Jason's research hones in on the pivotal task of estimating camera poses for 3D reconstruction - a challenge made more complex with sparse views. His paper proposes an inventive and out-of-the-box representation that perceives camera poses as a bundle of rays. This innovative perspective makes a substantial impact on the issue at hand, demonstrating promising results even in the context of sparse views.
What's particularly exciting is that his work, be it regression-based or diffusion-based, showcases top-notch performance on camera pose estimation on CO3D, and effectively generalizes to unseen object categories as well as captures in the wild.
Throughout our conversation, Jason explained his insightful approach and how the denoising diffusion model and set-level transformers come into play to yield these impressive results. I found his technique a breath of fresh air in the field of camera pose estimation, notably in the formulation of both regression and diffusion models.
On a more personal note, Jason and I didn't know each other before this podcast, so it was fantastic learning about his journey from the Bay Area to Pittsburgh. His experiences truly enriched our discussion and coined one of our most memorable episodes yet.
We hope you find this podcast as enlightening as we did creating it. If you enjoyed our chat, don't forget to subscribe for more thought-provoking discussions with early career academics and PhD students. Leave a comment below sharing your thoughts on Jason's paper!
Until next time, keep following your curiosity and questioning the status quo.
#TalkingPapersPodcast #ICLR2024 #CameraPoseEstimation #3DReconstruction #RayDiffusion #PhDResearchers #AcademicResearch #CarnegieMellonUniversity #BayArea #Pittsburgh
All links and resources are available in the blogpost: https://www.itzikbs.com/cameras-as-rays
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