📢SceneFactor code is released! SceneFactor is a factored latent diffusion for controllable, large-scale scene synthesis and editing! w/ @QTDSMQ, @shubhtuls, @angelaqdai Check out the code here: https://t.co/tJFRAPXKEI. We present SceneFactor at #CVPR2025 on Fri 13, -10:30

📢Animating the Uncaptured 📢 We animate 3D humanoid meshes using video diffusion priors given a text prompt. 🎥 https://t.co/EpFW86gaRw 🌍 https://t.co/suMQs8oQCL Realistic motion generation for 3D characters - without motion capture! 🚀 Great work by @marcbenedi @angelaqdai

📢ExCap3D: Multilevel Captioning of Objects in 3D Scenes @chandan__yes generates consistent object and part-level descriptions of objects in 3D scenes, and introduces a new dataset with 190k captions for 34k ScanNet++ objects. Project: https://t.co/6tWzlYsx5F w/ @david_roz_

📢 ScanNet++ v2 Benchmark Release! 🏆 Test your state-of-the-art models on: 🔹 Novel View Synthesis 📸➡️🖼️ 🔹 3D Semantic & Instance Segmentation 🤖🔍🕶️ Shoutout to @chandan__yes and @liuyuehcheng for their incredible work👏 🚀Check it out: https://t.co/SKCGM23hA0

📢MeshArt: Generating Articulated Meshes with Structure-guided Transformers @DaoyiGao generates articulated meshes with a hierarchical transformer, modeling articulation-aware structures that guide mesh synthesis. w/ @yawarnihal @craigleili Project: https://t.co/aZPVyn8kQd

Excited to announce ScanNet++ v2!🎉 @chandan__yes and @liuyuehcheng have been working tirelessly to bring: 🔹1006 high-fidelity 3D scans 🔹+ DSLR & iPhone captures 🔹+ rich semantics Elevating 3D scene understanding to the next level!🚀 w/ @MattNiessner https://t.co/QayR1S8KZZ

📢📢𝐆𝐀𝐅: 𝐆𝐚𝐮𝐬𝐬𝐢𝐚𝐧 𝐀𝐯𝐚𝐭𝐚𝐫 𝐑𝐞𝐜𝐨𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧 𝐟𝐫𝐨𝐦 𝐌𝐨𝐧𝐨𝐜𝐮𝐥𝐚𝐫 𝐕𝐢𝐝𝐞𝐨𝐬 𝐯𝐢𝐚 𝐌𝐮𝐥𝐭𝐢-𝐯𝐢𝐞𝐰 𝐃𝐢𝐟𝐟𝐮𝐬𝐢𝐨𝐧📢📢 We reconstruct animatable Gaussian head avatars from monocular videos captured by commodity devices such as

📢DNF: Generating 4D animations with dictionary-based neural fields! @xinyi092298 presents a new dictionary-based neural field for unconditional 4D generation of deforming shapes -- generating motions with high-quality shape and temporal consistency. https://t.co/yAZi2k0PjB

I'm so excited to introduce SceneFactor!

📢📢 𝐆𝐚𝐮𝐬𝐬𝐢𝐚𝐧𝐒𝐩𝐞𝐞𝐜𝐡: Audio-Driven Gaussian Avatars 📢📢 We synthesize photorealistic and 3D-consistent talking human head avatars driven directly from spoken audio. More specifically, we introduce an efficient 3DGS-based representation, combined with an

How can we generate high-fidelity, complex 3D scenes? @QTDSMQ's LT3SD decomposes 3D scenes into latent tree representations, with diffusion on the latent trees enabling seamless infinite 3D scene synthesis! w/ @craigleili, @MattNiessner https://t.co/wv9bIhkkYi

Excited to present DiffCAD coming to #SIGGRAPH2024! @DaoyiGao introduces the first probabilistic single-view CAD retrieval & alignment. We train only on synthetic -> generalize robustly to real images! Check out the code: https://t.co/hBCoN0Hx3w w/@david_roz_, @StefanLeuteneg1

Excited to present GenZI at #CVPR2024! @craigleili introduces GenZI, the first zero-shot approach to creating realistic 3D human-scene interactions by leveraging interaction priors from large VLMs. Code and data on our website! https://t.co/hUhMgUoU70 https://t.co/rnn1G5HOuu

AutoInst: Automatic Instance-Based Segmentation of LiDAR 3D Scans A method for unsupervised instance segmentation of 3D outdoor LiDAR scenes. Project: https://t.co/m8DJanWH2T Vid: https://t.co/Z9OyZbskdJ Paper : https://t.co/rrmvQdjmWV

Check out our #CVPR'24 papers on 3D human interactions, generative 3D modeling, and uncertainty-aware and unsupervised 3D semantic scene understanding! Congrats to @craigleili @david_roz_ @chrdiller @yawarnihal @shivangi2201 @jiapeng_tang @AnhQuanCAO for their amazing work!

Check out @chrdiller's CG-HOI :) We generate realistic 3D human-object interactions, from object geometry and text description. A key ingredient is explicit modeling of contact, during training and as guidance during inference. https://t.co/Cl5Jw9oFBO https://t.co/FVIFqEpjHi

Diffusion models are awesome! Check out our survey on 𝐃𝐢𝐟𝐟𝐮𝐬𝐢𝐨𝐧 𝐌𝐨𝐝𝐞𝐥𝐬 𝐟𝐨𝐫 𝐕𝐢𝐬𝐮𝐚𝐥 𝐂𝐨𝐦𝐩𝐮𝐭𝐢𝐧𝐠! We give an introduction to diffusion models and highlight how they are used by state-of-the-art methods in graphics and vision. https://t.co/FqaqF7tMPM

We've released the ScanNet++ data! Check it out: https://t.co/SKCGM23hA0 280 high-fidelity 3D scenes w/ 1mm geometry, DSLR+iPhone images, semantics We're currently beta-testing, please bear with us - approval may initially take up to 2 weeks Test scenes and benchmark to come!

Can we match visual features jointly across multiple frames? Yes! @barbara_roessle's #ICCV2023 paper proposes a differentiable pose optimization for end2end feature matching across multiple frames, thus obtaining better poses! https://t.co/CCYtA5PxCS https://t.co/cM0gaG3ids