📢 Gen3DSR: Generalizable 3D Scene Reconstruction via Divide and Conquer from a Single View .🌐 Project page: 📄 Paper: 👩‍💻 Code: Compositional 3D reconstruction of complex scenes with unprecedented quality🧵

RT @VisionBernie: We proudly present the static spin illusion - a finalist of the Best Illusion of The Year Contest. You perceive a rotatio….

The most fun image & video creation tool in the world is here. Try it for free in the Grok App.

RT @TheGraphicsFrog: 🔷🦀 TetWeave: Isosurface Extraction using On-The-Fly Delaunay Tetrahedral Grids for Gradient-Based Mesh Optimization is….

Had a great experience presenting our work on 3D scene reconstruction from a single image with @VisionBernie at #3DV2025 🇸🇬. Reach out if you're interested in discussing our research or exploring international postdoc opportunities @CogCoVi @UniFAU

RT @manuel_dahnert: Super happy to present our #NeurIPS paper 𝐂𝐨𝐡𝐞𝐫𝐞𝐧𝐭 𝟑𝐃 𝐒𝐜𝐞𝐧𝐞 𝐃𝐢𝐟𝐟𝐮𝐬𝐢𝐨𝐧 𝐅𝐫𝐨𝐦 𝐚 𝐒𝐢𝐧𝐠𝐥𝐞 𝐑𝐆𝐁 𝐈𝐦𝐚𝐠𝐞 in Vancouver. Come to o….

Plus, you'll join VCE, an awesome community with diverse research interests👩‍💻and fun team-building events like BBQs 🍽️, puzzle breaks 🧩, and baking competitions 🍪. Don’t miss out! .#ResearchOpportunity #PostDoc #PhD 2/2.

Highly recommend applying for this position! After working with @VisionBernie for two years as a PhD student, I can say he's an amazing advisor—very supportive, innovative, and well-connected. 1/2.

RT @takuma2460: Thrilled to share our work: 𝐀𝐫𝐂𝐒𝐄𝐌: Artistic Colorization of SEM Images via Gaussian Splatting . Novel view synthesis of s….

RT @_linus_franke: Happy to share our paper: "Refinement of Monocular Depth Maps via Multi-View Differentiable Rendering". TL;DR: Monocular….

RT @benno_bshmn: I'm looking forward to presenting RANRAC: Robust Neural Scene Representations via Random Ray Consensus @eccvconf next week….

RT @maxweiherer: Matérn Kernels for Tunable Implicit Surface Reconstruction. Paper: We use Matérn kernels for 3D s….

RT @TimoteiArdelean: Our poster @timweyrich is still up at #SIGGRAPH2024, you are welcome to come by and check it out if you didn't have th….

Work with @ozermert66 and @VisionBernie at @CogCoVi @UniFAU, where we have two year fully-funded postdoc positions open on related topics. (5/5).

We handle occlusions by employing amodal completion for each instance. The completed instance is then reconstructed using existing models that perform well for single objects. However, we first address the object crop domain shift (e.g., focal length) through reprojection. (4/5)

First, we parse the image of the scene by identifying the composing entities and estimating the depth and camera parameters. Each instance is then processed individually. The unprojected depth serves as a layout reference for composing the scene in 3D space. (3/5)

Most single-image scene-level reconstruction methods require 3D supervised end-to-end training and suffer from poor generalization capabilities. We propose a modular approach where each component performs well by focusing on specific tasks that are easier to supervise. (2/5).

RT @VisionBernie: How can we learn a multi-modal neural radiance field? What’s the best way to integrate images from a second modality, oth….

RT @gcpr_by_dagm: Got unfortunate news from #ECCV2024 (and waited too long to load the paper id list)? Consider sending the (slightly revis….

RT @TimoteiArdelean: #CVPR2024 has now come to an end. It was a great conference and I am glad I could be part of it, presenting our work @….

RT @_akhaliq: FAU Erlangen-Nürnberg presents TRIPS. Trilinear Point Splatting for Real-Time Radiance Field Rendering. paper page: https://t….