Très belle édition, merci pour le partage ! D'autres du genre à recommander ? Je suis à la recherche de tous les numéros de la revue Sœurs, pour ce combo illustration et poésie que j'apprécie beaucoup.
Positions remain open! Both PhD and postdoctoral opportunities are available on scientific foundation models. An additional position is also available on AI for regional climate models (jointly with @xavierfettweis.bsky.social). Do not hesitate to apply!
Actually o could be replaced by any point on the line :)
Not exactly what you're saying, but I like this piece about being at ease with our own ignorance to do good research: web.stanford.edu/~fukamit/sch...
The two postdoctoral positions remain open! (the PhD position has been filled) Applications from deep learning researchers or atmospheric scientists are welcome! Ping me if you have any questions!
Diverse in title 💥 I hope DaD loves soccer!
Nice of you! According to governments and media, it's an endangered species, very difficult to find them these days
Now I expect to read something like "The end of the Pointriarchy: how diverse correspondences lead to better deconstruction".
I understand Paul's post as concerns about "true things we can't say" anymore due to moralism and this thread about avoiding to publish because of the fear to be called out. Seemed potentially different to me
Now that you have, I'm curious to know if you agree with Paul's conclusion ?
Pretty cool article in NYT as well : rd.nytimes.com/projects/gau...
Our newest SoccerNet challenge on Monocular Depth Estimation is up and running! 🥳
Our world is 3D, football games are too, do you have what it takes to lift football analysis from 2D to 3D? 🏟️⚽️
I wish I stumbled on this pretty and clear intro to CUDA and GPUs years ago : modal.com/gpu-glossary
2⃣🚀 #SoccerNet2025 Let's present our Challenge #2: “Game State Reconstruction”
🏟 Reconstruct a schematic state of the game over time, capturing key player positions and overall game dynamics!
🔗 soccer-net.org/challenges/2...
#AIChallenge #SportsAnalytics @cvprconference.bsky.social
Broadcasting standards agree!
At #SIGGRAPHAsia, I just saw a paper talk where many of the examples shown are about making videos of women in short skirts and gym clothes dance to whatever sequence you want from a single image. How does this get published?
In the paper, they propose different methods for the LO step, two of them are advised depending on the use case. And there's also a follow-up paper LO+RANSAC...
Most SISR methods lately:
"This new method boasts a jaw-dropping 0.02 PSNR gain and was validated on, wait for it, 19 images. Truly the stuff of legends. 😂 #ScienceIsAwesome #InnovateOrDie"
Our paper "𝟑𝐃 𝐂𝐨𝐧𝐯𝐞𝐱 𝐒𝐩𝐥𝐚𝐭𝐭𝐢𝐧𝐠: 𝐑𝐚𝐝𝐢𝐚𝐧𝐜𝐞 𝐅𝐢𝐞𝐥𝐝 𝐑𝐞𝐧𝐝𝐞𝐫𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝟑𝐃 𝐒𝐦𝐨𝐨𝐭𝐡 𝐂𝐨𝐧𝐯𝐞𝐱𝐞𝐬” is now available on Arxiv!
💻Project page for some cool visualizations: convexsplatting.github.io
📓 Paper: arxiv.org/abs/2411.14974
Check out this BEAUTIFUL interactive blog about cameras and lenses
ciechanow.ski/cameras-and-...
🚀 🌟 #SoccerNet Challenges 2025 are here! In this 5th edition, we’re excited to unveil four diverse tasks!
⚽️ Check the deadline, there’s plenty of time to craft a groundbreaking solution and rise to the top of the leaderboard! 🏆
🔥Let the Challenges begin! #CVPR2025
SPARS3R: Semantic Prior Alignment and Regularization for Sparse 3D Reconstruction
Yutao Tang, Yuxiang Guo, Deming Li, Cheng Peng
tl;dr: align Mast3r to colmap point cloud, align outliers separately, as per semantic group -> splat
arxiv.org/abs/2411.12592
DGTR: Distributed Gaussian Turbo-Reconstruction for Sparse-View Vast Scenes
Hao Li, et al.
tl;dr: scene->non-overlap regions->sparse images->Splatt3R+global alignment+depth priors->initialization->local GS models->distillation-based model aggregation
arxiv.org/pdf/2411.12309
Hi Kosta ! Nice list
Can you add me ?
Future Bsky homes for our #computervision conferences!
@cvprconference.bsky.social
@iccv.bsky.social
@eccv.bsky.social
@wacvconference.bsky.social
Stay tuned!
Yes I confess I do
Yes very interested!
Image Matching Filtering and Refinement by Planes and Beyond
Fabio Bellavia, Zhenjun Zhao, Luca Morelli, Fabio Remondino
tl;dr: refine matches by estimating local homographies with special parameterization MiHo and NCC.
Improves even LG/LoFTR. Many additional analyses.
arxiv.org/abs/2411.09484
