PAGE-4D: Disentangled Pose and Geometry Estimation for 4D Perception Kaichen Zhou, Yuhan Wang, Grace Chen, Xinhai Chang, Gaspard Beaudouin, @fnzhan0507, Paul Pu Liang, Mengyu Wang tl;dr: dynamic VGGT https://t.co/NK7LEkKkr9

Advances in Feed-Forward 3D Reconstruction and View Synthesis: A Survey Jiahui Zhang, Yuelei Li, @AnpeiC, Muyu Xu, Kunhao Liu, @jianyuan_wang, @xxlong0, @hx_liang95, @zexiangxu, @haosu_twitr, Christian Theobalt, Christian Rupprecht, Andrea Vedaldi, @hpfister, Shijian Lu,

Advances in Feed-Forward 3D Reconstruction and View Synthesis: A Survey Abstract (excerpt): This survey offers a comprehensive review of feed-forward techniques for u3D reconstruction and view synthesis. It provides a taxonomy based on underlying representation architectures,

Submit your extended abstract to our workshop on "Generative Models for Computer Vision" #CVPR2025 @CVPR Authors with accepted CVPR papers are welcome to present their poster as well! Deadline: April 25th We also have an incredible speaker line-up!

Visual Acoustic Fields Contributions: • The impact locations of collected visual-sound pairs can be localized in 3D space by learning a radiance field with synchronized camera poses. • Predicted impact sounds in our Visual Acoustic Fields accurately align with the

I've never seen a more polished paper teaser video than this one. The 3D Gaussians even cast shadows!

📢Our latest preprint shows that learning global neuron shapes can help to automatically proofread connectomes and predict neuron types. https://t.co/v39Zm5Igo1 Work done in collaboration with @HHMIJanelia, @srinituraga & @HarvardVCG #connectomics #AI 🧵(1/n)

Fully packed 🥳

Join our workshop on Neural Rendering Intelligence today at 1:30 pm in Summit 332 to see the latest advances in neural rendering! Exciting keynote speakers! More info at https://t.co/wRN0jA34sx @BenMildenhall @GordonWetzstein @vincesitzmann @yiyi_liao_ @MattNiessner @haosu_twitr

The Neural Rendering workshop will take place at #CVPR2024 in Seattle! @CVPR https://t.co/wRN0jA34sx Organized by @fnzhan0507 @AnpeiC @AdamKortylewski @_atewari @SiyuTang3 Christian Theobalt We have a fantastic speaker line-up!

Submit your short or long papers to our workshop on ""Generative Models for ComputerVision" @CVPR #CVPR2024 The deadline is March 27th. We also have a fantastic speaker line-up! @fedassa @jiajunwu_cs @sainingxie @SiyuTang3 @Jamie_Shotton @YuilleAlan @deviparikh K.Fragkiadaki

"StyleGaussian: Instant 3D Style Transfer with Gaussian Splatting" Project: https://t.co/9Z6Hcf2Y9P Paper: https://t.co/cQfiKHj6kU

Submissions are now open for our workshop on Generative Models for Computer Vision! @CVPR #CVPR2024 We also have an initial line-up of keynote speakers. https://t.co/2TGy7r24GT @fnzhan0507 @LingjieLiu1 @Mi_Niemeyer @mjoech @YuilleAlan @VcaiMpi

Super happy that the 2nd edition of our workshop on "Generative Models for Computer Vision" got accepted to #CVPR2024 We again have a fantastic lineup of keynote speakers, stay tuned! Kudos to @fnzhan0507 @LingjieLiu1 @Mi_Niemeyer @mjoech @YuilleAlan Christian Theobalt @VcaiMpi

DatasetNeRF: Efficient 3D-aware Data Factory with Generative Radiance Fields Yu Chi, Fangneng Zhan, Sibo Wu, Christian Theobalt, @AdamKortylewski tl;dr: in title https://t.co/Ue7OwrjrTW

Check out our TPAMI 2023 survey paper on visual AIGC and multimodal generation, delving into GANs, diffusion models, autoregressive models, and NeRFs. Project page: https://t.co/gx95FXPMgZ GitHub: https://t.co/fe2uGc4rKb Paper: https://t.co/bfBiRLD92p

General Neural Gauge Fields Fangneng Zhan, @LingjieLiu1 , @AdamKortylewski , Christian Theobalt tl;dr: jointly end-to-end learn gauge transformation and neural fields https://t.co/Ku32dFLkK5

Submissions are now open for our workshop on Generative Models for Computer Vision @CVPR #CVPR2023 https://t.co/eekWbdxIng

Thrilled that our workshop on "Generative Models for Computer Vision" got accepted to #CVPR2023! We have a fantastic speaker lineup with whom we will discuss how image synthesis can benefit image analysis. Stay tuned! :-)

Strongly disagree with the first one. "What I cannot create I cannot understand" - Richard Feynman. Generative AI is not just for creating fun art, it is at the core of concept learning.