Gaurav Singh @gauravsinghk03
Incoming PhD student @BrownCSDept vanhalen42.github.io Joined February 2017-
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Check out new work on scene completion and grasping from a single RGB-D image!
Check out new work on scene completion and grasping from a single RGB-D image!
Our technical report is here: arxiv.org/abs/2411.00704 šš SOUND ON!! Here's a clip of you coming back home to š¤ Frank š¤setting up your dinner table š«šš²š„š¢
Our technical report is here: arxiv.org/abs/2411.00704 šš SOUND ON!! Here's a clip of you coming back home to š¤ Frank š¤setting up your dinner table š«šš²š„š¢ https://t.co/s9eWGC0wGv
šExcited to share SceneComplete: an open-world 3D scene completion system for constructing a complete, segmented 3D model of a scene from a single RGB-D image.š¼ļøš¤ SceneComplete enables dexterous grasping and robust robot manipulation in highly cluttered scenes - a short š§µ
š Introducing Frank š¤āa whole-body robot control system for day-to-day household chores. Frank has been in works for the past yearāa tightly coupled hardware and a remote teleoperation interface co-led by @michl_wang, @nst372, and @pulkitology. Thanks to @skymanaditya1 andā¦
At @CVPR, I will be giving two workshop keynotes tomorrow (June 18). At the C3DV workshop, I will talk about our group's recent work on Compositional 3D Understanding and Editing. Summit 327, at 1:00 PM. 3dcompat-dataset.org/workshop/C3DV2ā¦
Students at @iiit_hyderabad, supposed to be one of the top engineering colleges in the country, are in an ongoing health crisis caused due to appalling mismanagement and negligence going on since well over a year. š§µšon mass typhoid breakouts, food poisoning, underreporting..
New paper: The Platonic Representation Hypothesis In which we posit that _different_ foundation models are converging to the _same_ representation of reality. paper: arxiv.org/abs/2405.07987 website: phillipi.github.io/prh/ code: github.com/minyoungg/plat⦠1/8
Are game engines world simulators? Given a mesh+texture, a game can render a beautiful depiction of tree bark. But, typically, it doesn't model how the bark came to be in the first place, how the mesh+texture were created. Gen models, in a sense, do. 1/3
Had a lot of fun presenting my paper at @NeurIPSConf with @bipashasen31 and @skymanaditya1. Also met @ylecun!!!
HyP-NeRF is a generalizable NeRF prior that allows reconstruction from sparse inputs like a single image or text descriptions. Come see our poster #438 @NeurIPSConf. Tue 12 Dec 3:15 p.m. PST - 5:15 p.m. PST, Great Hall & Hall B1+B2 (level 1) .
HyP-NeRF is a generalizable NeRF prior that allows reconstruction from sparse inputs like a single image or text descriptions. Come see our poster #438 @NeurIPSConf. Tue 12 Dec 3:15 p.m. PST - 5:15 p.m. PST, Great Hall & Hall B1+B2 (level 1) .
Excited to share "HyP-NeRF" recently accepted to #NeurIPS2023! HyP-NeRF doesn't do just one thing -- it does many things!! It can generate NeRFs (directly the parameters!) from text, single-view, and multi-view (occluded/non-occluded) images! Page: hyp-nerf.github.io š
HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork Bipasha Sen, Gaurav Singh, Aditya Agarwal, Rohith Agaram, K Madhava Krishna, Srinath Sridhar tl;dr: hypernetworks->MLP weights+instance-specific hash encodings arxiv.org/pdf/2306.06093ā¦
šØIntroducing HyP-NeRF (accepted to #NeurIPS2023), a latent conditioning method for learning generalizable category-level NeRF priors using hypernetworks! We enable several tasks -- reconstruction from single-view unposed image, text-to-NeRF, & object retrieval from clutter!

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