Visual Intelligence Lab @ucsd_cse @UCSanDiego (Prof. Manmohan Chandraker and students)
Joined April 2021
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22 Photos and videos
27 Sep 2023
Join us at #ICCV2023 in Paris for the inaugural workshop on Robust Computer Vision Across Geographies, which includes keynotes by an exciting line-up of speakers, and oral talks by the winners of the GeoNet domain adaptation challenge!
Website: geonet-challenge.github.io/I…
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23 Aug 2023
The test-set for the #GeoNet challenge has been released, and the submission portal for the challenge is now active!
Registration Link: forms.gle/zSZA1iaPD3mZxjyn7
Leaderboard: eval.ai/web/challenges/chall…
The deadline for the submission is September 5th.
#ICCV2023
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21 Jun 2023
The GeoNet dataset will be presented at #CVPR2023 during the Wed PM poster session (#287), do drop by to know more about the efforts to improve geographical robustness of vision models @ViLabUCSD.
Paper Webpage: tarun005.github.io/GeoNet/
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6 Apr 2023
Check out our new #CVPR2023 paper and dataset GeoNet, that explores challenges for robust and fair computer vision across geographies!
Webpage: tarun005.github.io/GeoNet/
PDF: arxiv.org/abs/2303.15443
Work done by @tarun_05, wangdong_xu and @manu_chandraker at @ucsd_cse.
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ViLab UCSD retweeted
26 Oct 2022
Delighted to receive the Best Paper Honorable Mention @eccvconf #ECCV2022 for Neural Implicit Evolution, together with @ishit_mehta and Ravi Ramamoorthi @ucsd_cse @UCSanDiego @ViLabUCSD
Code and webpage: ishit.github.io/nie/
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24 Oct 2022
🗓️ 10/25 Oral at 1:30 PM (Hall E). Poster 115 at 3:30 (Hall B).
Physically-Based Editing of Indoor Scene Lighting from a Single Image.
Zhengqin Li, @manu_chandraker et. al.
Estimate visible and invisible light sources for indoor scene relighting !
bit.ly/3MY8TaB
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24 Oct 2022
🗓️ 10/27 Poster 27 at 11:00 AM (Hall B).
MemSAC: Memory Augmented Sample Consistency
for Large Scale Domain Adaptation
@tarun_05 @AstutiSharma @manu_chandraker
Cross-domain sample consistency approach to scale domain adaptation to large-scale datasets.
tarun005.github.io/MemSAC/
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28 Jul 2022
Check out our new work on level-set evolution of neural implicit surfaces. It allows energy formulations on triangle meshes to be used to deform neural implicits. A variety of explicit differentiable rendering and surface algorithms can now be used with free topological changes.
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28 Jul 2022
We anticipate potential applications in 3D reconstruction, inverse rendering, shape optimization, etc.
We will be at #ECCV2022 with an oral presentation. Project and code are at ishit.github.io/nie
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28 Jul 2022
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24 Jun 2022
Excited to share #PhotoScene at #CVPR2022 for creating photorealistic 3D digital twins from images! Chat with us (in-person!!) at poster session 4.1 during 10:00-12:30 on June 24 (Fri) and see our project page for more details!
Project page: yuyingyeh.github.io/projects…
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21 Jun 2022
Excited to invite you all to the oral talk (session 1.2, 1:30 PM, in-person!) of our paper #IRISFormer at #CVPR2022, where we propose a dense #transformer for single image inverse rendering.
Also find us at the poster session 1.2 to learn more about #IRISFormer and chat with us!
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22 Jun 2021
Check out #OpenRooms being released by @ViLabUCSD at #CVPR2021, an open framework for creating photorealistic counterparts of indoor 3D scans, with ground truth geometry, material, lighting, semantics and physical properties.
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22 Jun 2021
Check out the project page, the #CVPR2021 oral paper and other details here:
vilab-ucsd.github.io/ucsd-op….
Please visit our poster at #CVPR2021 on Wed, June 23, 2021 6:00– 8:30 EDT for more details. (PaperId: 10082).
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22 Jun 2021
Joint work by @LiZhengqin, Ting-Wei Yu, Shen Sang, Sarah Wang, Meng Song, Yuhan Liu, @YuYingYeh1, Rui Zhu, Nitesh Gundavarapu, Jia Shi, Sai Bi, Zexiang Xu, Hong-Xing Yu, Kalyan Sunkavalli, Miloš Hašan, Ravi Ramamoorthi, @manu_chandraker .
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