Chris Rockwell @_crockwell
PhD student in #ComputerVision at @UmichCSE Views are my own. crockwell.github.io Ann Arbor, MI Joined March 2013-
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Hello! If you are interested in dynamic 3D or 4D, don't miss the oral session 3A at 9 am on Saturday: @zhengqi_li will be presenting "MegaSaM" I'll be presenting "Stereo4D" and @QianqianWang5 will be presenting "CUT3R"
Excited to share our CVPR 2025 paper on cross-modal space-time correspondence! We present a method to match pixels across different modalities (RGB-Depth, RGB-Thermal, Photo-Sketch, and cross-style images) — trained entirely using unpaired data and self-supervision. Our…
Ever wondered how a scene sounds👂 when you interact👋 with it? Introducing our #CVPR2025 work "Hearing Hands: Generating Sounds from Physical Interactions in 3D Scenes" -- we make 3D scene reconstructions audibly interactive! yimingdou.com/hearing_hands/
Can AI image detectors keep up with new fakes? Mostly, no. Existing detectors are trained using a handful of models. But there are thousands in the wild! Our work, Community Forensics, uses 4800+ generators to train detectors that generalize to new fakes. #CVPR2025 🧵 (1/5)
Hello! If you like pretty images and videos and want a rec for CVPR oral session, you should def go to Image/Video Gen, Friday at 9am: I'll be presenting "Motion Prompting" @RyanBurgert will be presenting "Go with the Flow" and @ChangPasca1650 will be presenting "LookingGlass"
Cameras are key to modeling our dynamic 3D visual world. Can we unlock the 𝘥𝘺𝘯𝘢𝘮𝘪𝘤 3𝘋 𝘐𝘯𝘵𝘦𝘳𝘯𝘦𝘵?! 🌎 📸 𝗗𝘆𝗻𝗣𝗼𝘀𝗲-𝟭𝟬𝟬𝗞 is our answer! @_crockwell has curated Internet-scale videos with camera pose annotations for you 🤩 Download: huggingface.co/datasets/nvidi…
Cameras are key to modeling our dynamic 3D visual world. Can we unlock the 𝘥𝘺𝘯𝘢𝘮𝘪𝘤 3𝘋 𝘐𝘯𝘵𝘦𝘳𝘯𝘦𝘵?! 🌎 📸 𝗗𝘆𝗻𝗣𝗼𝘀𝗲-𝟭𝟬𝟬𝗞 is our answer! @_crockwell has curated Internet-scale videos with camera pose annotations for you 🤩 Download: huggingface.co/datasets/nvidi…
Video generation models exploded onto the scene in 2024, sparked by the release of Sora from OpenAI. I wrote a blog post on key techniques that are used in building large video generation models: yenchenlin.me/blog/2025/01/0…
Introducing 👀Stereo4D👀 A method for mining 4D from internet stereo videos. It enables large-scale, high-quality, dynamic, *metric* 3D reconstructions, with camera poses and long-term 3D motion trajectories. We used Stereo4D to make a dataset of over 100k real-world 4D scenes.
What happens when you train a video generation model to be conditioned on motion? Turns out you can perform "motion prompting," just like you might prompt an LLM! Doing so enables many different capabilities. Here’s a few examples – check out this thread 🧵 for more results!
We present Global Matching Random Walks, a simple self-supervised approach to the Tracking Any Point (TAP) problem, accepted to #ECCV2024. We train a global matching transformer to find cycle consistent tracks through video via contrastive random walks (CRW).
📢 Introducing our #ECCV2024 work, COCO-ReM (COCO Refined Masks), for more reliable benchmarking of object detectors, crucial for the future of object detection research. Paper: arxiv.org/abs/2403.18819 Code: arxiv.org/abs/2403.18819 Website: cocorem.xyz
📢Presenting 𝐃𝐄𝐏𝐈𝐂𝐓: Diffusion-Enabled Permutation Importance for Image Classification Tasks #ECCV2024 We use permutation importance to compute dataset-level explanations for image classifiers using diffusion models (without access to model parameters or training data!)
Excited to present our #CVPR2024 *Highlight* FAR on Friday at 10:30 a.m, Arch 4A-E Poster #31. Please feel free to stop by! FAR significantly improves correspondence-based methods using end-to-end pose prediction, making it applicable to many SOTA approaches!
Excited to present our #CVPR2024 *Highlight* FAR on Friday at 10:30 a.m, Arch 4A-E Poster #31. Please feel free to stop by! FAR significantly improves correspondence-based methods using end-to-end pose prediction, making it applicable to many SOTA approaches!
We've curated a 1-million 3D-Captioning dataset for Objaverse(-XL), correcting 200k potential misalignments in the original Cap3D captions. Our method employs a pre-trained text-to-3D model to rank rendered views and utilizes GPT-4 Vision. Each caption is linked to a point…
Lightplane gives 1000x memory saving for differentiable rendering and feature splatting (i.e. unprojecting 2D features to 3D), which is generalizable to a variety of 3D structures. We hope it could solve memory bottleneck in current 3D pipeline and contribute to 3D research.
Lightplane gives 1000x memory saving for differentiable rendering and feature splatting (i.e. unprojecting 2D features to 3D), which is generalizable to a variety of 3D structures. We hope it could solve memory bottleneck in current 3D pipeline and contribute to 3D research.
Jim Fan @DrJimFan
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Leo Bringer @leo_bringer
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Yayuan Li @YayuanLi
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722 Followers 302 Following PhD Student @tumcvg, Prev Intern @Meta GenAI, MSc CompSci @UniofOxford, 3D Computer Vision, https://t.co/wh6ywxLvUW
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519 Followers 198 Following phd student at 3DV group, CAD&CG @ZJU_China; focus on 3D Vision&Graphics&Robotics. https://t.co/sW3SRt1IG7
NuomiAI @NuomiAI
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Paul Fadieiev @pavlo_fadieiev
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AK @_akhaliq
428K Followers 3K Following AI research paper tweets, ML @Gradio (acq. by @HuggingFace 🤗) dm for promo ,submit papers here: https://t.co/UzmYN5YmrQ
Kosta Derpanis @CSProfKGD
68K Followers 197 Following #CS Assoc Prof @YorkUniversity, #ComputerVision Scientist Samsung #AI, @VectorInst Faculty Affiliate, TPAMI AE, @ELLISforEurope Member #ICCV2025 Publicity Chair
Matthias Niessner @MattNiessner
41K Followers 241 Following Professor for Visual Computing & Artificial Intelligence @TU_Muenchen Co-Founder @synthesiaIO Co-Founder @SpAItial_AI
Dmytro Mishkin 🇺�... @ducha_aiki
24K Followers 706 Following Marrying classical CV and Deep Learning. I do things, which work, rather than being novel, but not working.
Andrej Karpathy @karpathy
1.4M Followers 1K Following Building @EurekaLabsAI. Previously Director of AI @ Tesla, founding team @ OpenAI, CS231n/PhD @ Stanford. I like to train large deep neural nets.
Jim Fan @DrJimFan
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Michael Black @Michael_J_Black
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Aran Komatsuzaki @arankomatsuzaki
145K Followers 302 Following Looking for a cofounder. Sharing AI research. Early work on AI (GPT-J, LAION, scaling, MoE). Ex ML PhD (GT) & Google.
Jia-Bin Huang @jbhuang0604
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Computer Science and ... @UMichCSE
4K Followers 251 Following Shaping the future through the power of computing.
Rada Mihalcea @radamihalcea
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Jon Barron @jon_barron
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Soumith Chintala @soumithchintala
252K Followers 1K Following Cofounded and lead @PyTorch at Meta. Also dabble in robotics at NYU. AI is delicious when it is accessible and open-source.
PyTorch @PyTorch
453K Followers 77 Following Tensors and neural networks in Python with strong hardware acceleration. PyTorch is an open source project at the Linux Foundation. #PyTorchFoundation
Rana Hanocka @RanaHanocka
6K Followers 385 Following Assistant Professor @uchicago @uchicagocs. PhD from @TelAvivUni. Interested in computer graphics, machine learning, & computer vision 🤖
Andrea Tagliasacchi �... @taiyasaki
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689 Followers 520 Following Ph.D. student at @Umich, previously @cohere, @allenai, @AmazonScience, and @NaverLabsEurope. Interested in LLM reasoning, verifiers, and web agents.
Zhenjun Zhao @zhenjun_zhao
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Dynamics Lab @DynamicsLab_AI
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Pierre Richemond 🇪... @TheOneKloud
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Alexander Kirillov @_alex_kirillov_
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