Manmohan Chandraker @manu_chandraker
Computer vision and machine learning Joined July 2020-
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Check out our #ICRA2024 talk on May 16, session ThBT9-CC, on long-horizon object transport (Long-HOT). It proposes an #EmbodiedAI task and method for a robotic agent to explore, navigate and transport objects in large spaces. Work led by @nnsriram97 and with @dineshjayaraman.
Congratulations, Yu-Ying Yeh, on a successful PhD thesis defense @ViLabUCSD @ucsd_cse ! Her amazing work on high-quality 3D content creation for mixed reality was also recognized with the Qualcomm Innovation and Google PhD Fellowships. All the best for the future, @YuYingYeh1 !
Check out my talk on our work on photorealism in indoor #AugmentedReality at the CV4AEC workshop at #CVPR2023, today at 11:30am. cv4aec.github.io
Check out the GeoNet paper and dataset that explore challenges for robust and fair computer vision across geographies. Work by @tarun_05 in collaboration with @wangdong_xu at @ViLabUCSD
Check out the GeoNet paper and dataset that explore challenges for robust and fair computer vision across geographies. Work by @tarun_05 in collaboration with @wangdong_xu at @ViLabUCSD
Faster slo-mo? In collaboration with CSE’s @manu_chandraker and @tarun_05 with former @metaai researchers @dutran and @pathak2206, FLAVR breaks new ground in video frame interpolation Check out slow-mo effect using FLAVR👇 Read more here: bit.ly/40bebVV
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/
🗓️ 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/
🗓️ 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
🗓️ 10/25 Oral at 1:30 PM (Hall E). Poster #80 at 3:30 PM (Hall B). A Level Set Theory for Neural Implicit Evolution under Explicit Flows @ishit_mehta @manu_chandraker Ravi R. A level-set theory bridge between explicit and implicit shape representations. ishit.github.io/nie
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/photo…
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!
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.
Organised in collaboration with IIIT-Hyderabad, IIT-Hyderbad, Intel and @ViLabUCSD
Also included during the workshop are presentations from the winners of the Unstructured Scene Understanding Challenge for Autonomous Navigation. Challenge and benchmark: cvit.iiit.ac.in/autonue2021/ch…
Our awesome line-up of speakers include @hiskov, @kate_saenko_, @kkitani, @AlexAlahi, Ang Marcelo and Ruigang Yang. Check out the full program here: cvit.iiit.ac.in/autonue2021/pr…
Join us at the #CVPR2021 workshop on Autonomous Navigation in Unconstrained Environments on June 19: cvit.iiit.ac.in/autonue2021/.
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