Alexey Bokhovkin

📢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: github.com/alexeybokhovki…. We present SceneFactor at #CVPR2025 on Fri 13, -10:30 PDT. Don't forget to drop by 😊

📢Animating the Uncaptured 📢 We animate 3D humanoid meshes using video diffusion priors given a text prompt. 🎥youtu.be/_YL1J_V3smI 🌍marcb.pro/atu 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: cy94.github.io/excap3d 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: kaldir.vc.in.tum.de/scannetpp/

📢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: daoyig.github.io/Mesh_Art/

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 kaldir.vc.in.tum.de/scannetpp

📢📢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 smartphones. Key idea: distill reconstruction constraints from a multi-view head diffusion model to complete unobserved regions. tangjiapeng.github.io/projects/GAF/ youtu.be/QuIYTljvhyg Great work by @jiapeng_tang @davidedavoli @TobiasKirschst1 @liamschoneveld

📢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. xzhang-t.github.io/project/DNF/

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 audio-conditioned transformer, to generate realistic and high-quality animations. Our method can easily generalize to a variety of in the wild scenarios like songs, foreign languages etc. We further introduce a new multiview dataset of native English speakers with overall recording time of ∼3.5 hours. Project: shivangi-aneja.github.io/projects/gauss… Video: youtu.be/2VqYoFlYcwQ Great work by @shivangi2201, @ASevastopolsky, @TobiasKirschst1, @JustusThies, @angelaqdai

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 quan-meng.github.io/projects/lt3sd/

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: daoyig.github.io/DiffCAD_/ 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! craigleili.github.io/projects/genzi/ youtu.be/ozfs6E0JIMY

AutoInst: Automatic Instance-Based Segmentation of LiDAR 3D Scans A method for unsupervised instance segmentation of 3D outdoor LiDAR scenes. Project: artonson.github.io/publications/2… Vid: youtube.com/watch?v=ioKJWY… Paper : arxiv.org/pdf/2403.16318…

@artonson Really nice work, congrats!

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. cg-hoi.christian-diller.de youtube.com/watch?v=GNyQwT…

@KatyaArtemov @TolokaAI Super cool! My warmest congratulations!

I’m happy to share that I’m starting a new position as NLP Researcher at @TolokaAI! Being a long-time requester on the Toloka platform, I am now excited to join the research team :)

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. arxiv.org/abs/2310.07204