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DTSTAMP:20260805T205507Z
LOCATION:Room 408 B
DTSTART;TZID=America/Los_Angeles:20260721T140000
DTEND;TZID=America/Los_Angeles:20260721T153000
UID:siggraph_SIGGRAPH 2026_sess147@linklings.com
SUMMARY:Computational Photography
DESCRIPTION:Guidestar-Free Adaptive Optics with Asymmetric Apertures\n\nWe
  introduce and demonstrate the first closed-loop adaptive optics system ca
 pable of optically correcting aberrations in real-time without a guidestar
  or a wavefront sensor. We enable these capabilities by combining asymmetr
 ic apertures, machine learning–based PSF estimation and phase retrieva...\
 n\n\nWeiyun Jiang and Haiyun Guo (Rice University); Christopher A. Metzler
  (University of Maryland, College Park); Ashok Veeraraghavan (Rice Univers
 ity); and Weiyun Jiang\n---------------------\nMAROON: A Dataset for the J
 oint Characterization of Near-Field High-Resolution Radio-Frequency and Op
 tical Depth Imaging Techniques\n\nRobust perception benefits from compleme
 ntary sensors, yet close-range setups remain scarce. We characterize optic
 al and near-field radar imagers via multimodal calibration, collecting dat
 a from RGB-D sensors and one mmWave MIMO radar. We evaluate depth sensing 
 across materials, geometries, and dist...\n\n\nVanessa Wirth, Johanna Bräu
 nig, Nikolai Hofmann, and Martin Vossiek (Friedrich-Alexander-Universität 
 Erlangen-Nürnberg); Tim Weyrich (Friedrich-Alexander-Universität Erlangen-
 Nürnberg, University College London); Marc Stamminger (Friedrich-Alexander
 -Universität Erlangen-Nürnberg); and Vanessa Wirth\n---------------------\
 nNon-line-of-sight imaging with arbitrary relay surface geometries via 3D 
 Gaussian Transient Rendering\n\nWe present a LOS-guided NLOS imaging pipel
 ine for arbitrary relay surface geometries, representing hidden scenes wit
 h 3D Gaussian primitives and developing an efficient differentiable transi
 ent renderer. Real experiments on complex relay surfaces captured with our
  custom system show improved robustn...\n\n\nYi Wang, Ziyu Zhan, and Yuran
  Wang (Tsinghua University); Hao Wang (City University of Hong Kong); and 
 Qiang Liu, Zuoqiang Shi, Lingyun Qiu, and Xing Fu (Tsinghua University)\n-
 --------------------\nBroadband Hyperspectral 3D Imaging using Dispersed S
 tructured Light\n\nWe present a broadband hyperspectral 3D (BH3D) imaging 
 system spanning visible to SWIR (450–1500 nm). Using a single-spectrograph
  stereo setup, our method jointly reconstructs accurate 3D geometry and ma
 terial properties, enabling robust analysis of real-world scenes beyond th
 e visible spectru...\n\n\nSuhyun Shin and Yunseong Moon (POSTECH), Ryota M
 aeda (University of Hyogo), David Lindell and Kyros Kutulakos (University 
 of Toronto), and Seung-Hwan Baek (POSTECH)\n---------------------\nGenPIE:
  A Time-Resolved Plenoptic Imager\n\nWe present a physically grounded gene
 rative imaging system to resolve high-dimensional, time-resolved plenoptic
  light transport from sparse measurements. Using decoupled laser-detector 
 capture, 3D foundation-model priors, and differentiable transient renderin
 g, we reveals indirect light transport fo...\n\n\nZiheng Wang (The Chinese
  University of Hong Kong, Shenzhen); Siyuan Shen and Huanyu Xu (ShanghaiTe
 ch University); Kaichun Qiao, Longwen Zhang, and Qixuan Zhang (ShanghaiTec
 h University, Deemos Technology); Qilin Sun (The Chinese University of Hon
 g Kong, Shenzhen; Point Spread Technology); and Shiying Li and Jingyi Yu (
 ShanghaiTech University)\n---------------------\nPolicy-based Foveated Ima
 ging and Perception\n\nUltra-high-resolution sensors capture fine details 
 critical for visual perception, but acquiring all pixels at full resolutio
 n is often infeasible under realistic constraints. We introduce a real-tim
 e, task-aware foveated imaging framework that learns a sensor attention po
 licy to dynamically allocat...\n\n\nHoward Xiao, Jan Ackermann, Boyang Den
 g, and Gordon Wetzstein (Stanford University)\n---------------------\nComp
 utational Photography - Interactive Discussion\n\nAfter the summary presen
 tations, attendees will participate in an interactive discussion. Outside 
 the room will be a series of poster boards for authors to gather around wi
 th the audience. Authors are invited to bring any material related to thei
 r paper that could instigate further conversation such...\n\n\nInterest Ar
 ea: Research & Education\n\nKeyword: Artificial Intelligence/Machine Learn
 ing\n\nRegistration Category: Full Conference Supporter, Full Conference\n
 \nSession Chair: Adithya Pediredla (Dartmouth College)
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