Computer vision researcher @evs & PhD student @universitedeliege.bsky.social
Our world is 3D, football games are too, do you have what it takes to lift football analysis from 2D to 3D? 🏟️⚽️
📹 Generate precise depth maps using only a single monocular camera and redefine soccer analysis!
With this, all four 2025 challenges are officially announced! 🧵 @cvprconference.bsky.social
Our world is 3D, football games are too, do you have what it takes to lift football analysis from 2D to 3D? 🏟️⚽️
🏟 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
🏟 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
"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"
"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"
💻Project page for some cool visualizations: convexsplatting.github.io
📓 Paper: arxiv.org/abs/2411.14974
💻Project page for some cool visualizations: convexsplatting.github.io
📓 Paper: arxiv.org/abs/2411.14974
⚽️ 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
⚽️ 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
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
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
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
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
@cvprconference.bsky.social
@iccv.bsky.social
@eccv.bsky.social
@wacvconference.bsky.social
Stay tuned!
@cvprconference.bsky.social
@iccv.bsky.social
@eccv.bsky.social
@wacvconference.bsky.social
Stay tuned!
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
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
Jonas Serych, Michal Neoral, Jiri Matas
tl;dr: algorithm for robust chaining optical flow in video + learned quality estimation module.
RoMA rules, SeaRAFT is second best.
arxiv.org/abs/2411.09551
Jonas Serych, Michal Neoral, Jiri Matas
tl;dr: algorithm for robust chaining optical flow in video + learned quality estimation module.
RoMA rules, SeaRAFT is second best.
arxiv.org/abs/2411.09551