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SIGGRAPH 2018 レポート
SIGGRAPH2018 is an annual computer graphics conference put on by the ACM SIGGRAPH group. It features technical papers, emerging technologies, exhibitions from industry, and sessions on computer graphics, vision, and VR/AR topics. This year's conference included demonstrations of virtual and augmented reality technologies from companies like Microsoft, Google, and NVIDIA. Emerging technologies showcased research on retinal projection, spherical displays, computational photography, and new input/output devices. The technical papers covered deep learning, image/video processing, 3D capture/reconstruction, and human-computer interaction including facial animation and VR locomotion.
SIGGRAPH 2018 レポート
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- 2. SIGGRAPH • Special InterestsGroup on Computer GRAPHics • Association for Computing Machinery( :ACM) CG • 1974 • ( ) • 160 16,637
- 3. SIGGRAPH ART GALLERY ART PAPERS BIRDSOF A FEATHER COMPUTER ANIMATION FESTIVAL ( VR) COURSES EMERGINGTECHNOLOGIES EXHIBITION INTERNATIONAL RESOURCES JOB FAIR KEYNOTE SESSION PANELS POSTERS SIGGRAPH NEXT STUDIO TECHNICAL PAPERS 3 ※Wikipedia(En), SIGGRAPH2018 HP
- 4. FULL CONFERENCE ($1,150)EXHIBITS PLUS ($150) EXHIBITS ONLY ($50) ART GALLERY ● ● - ART PAPERS ● - - BIRDS OF A FEATHER ● ● - COMPUTER ANIMATION FESTIVAL ● - - COURSES ● - - EMERGINGTECHNOLOGIES ● ● - EXHIBITION ● ● ● INTERNATIONAL RESOURCES ● ● - JOB FAIR ● ● ● KEYNOTE SESSION ● - - PANELS ● - - POSTERS ● ● - SIGGRAPH NEXT ● ● - STUDIO ● ● - TECHNICAL PAPERS ● - - ※ 7 Non-menber Early Bird
- 5. Exhibits Plus • • • →Web • ComputerVision,VR, Camera
- 6. ‣ ‣ VR/MR WebVRAPI2.0 NYU CAVE etc. ‣ (EmergingTech.) ‣ GPU (NVIDIA RTX ) ‣ VR ‣ Google Microsoft ‣
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- 9. Tastes Controller (, ) • GTS: Galvanic Tongue Stimulation • • VR/AR
- 10. Human Support Robot( TRI) • ROS •
- 11. HEADLIGHT;Wearable Projector (SonyCSL) • • 105° 55°
- 12. 2400fps ( ) •(400fps ) (2400fps) •
- 13. Realtime Non-Line-Of-Site Imaging(Stanford ) • SPAD Time Of Flight • LiDAR
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- 15. Make your ownRetinal Projector ( Pixie DustTechnologies) • (TMD) • TMD
- 16. TMD Near-Eye (Pixie DustTechnologies) • HMD TMD • OculusVR Developer Kit 3D
- 17. ( Pixie) • EMS •Arduino
- 18. Leviopole ( ) • VR •VR/AR
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- 21. Spherical FishTankVR Display(British Columbia Saskatchewan ) • •
- 22. Steerable Application-Adaptive Near-EyeDisplays (NVIDIA, UNC) • AR HMD • Norland Products Norland Optical Adhesives • EmergingTechnologies Best in Show
- 23. SEER (Stimulative EmotionalExpression Robot) • • TakayukiTodo
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- 26. VR Stereoscope (1838 ) Nintendo 3D Glasses (1987) SegaScope 3D Glasses (1988 ) Nintendo Power Glove (1989 )
- 27. VR Virtual Research HMD (1991 ) TakaraHMD Dynovisor (1994 ) Virtuality HMD (1994 ) VRontier World’s Tier 1 (1993 )
- 28. VR Tiger’s R-Zone (1995 ) Nintendo VirtualBoy (1995) Virtual iO Glasses (1995 ) Vuzix iWear VR920 (2007 ) Virtual Research HMD (1991 )
- 29. VR Oculus DK2 (2014 ) AvegantGlyph (2016 ) Google Cardboard (2014 )
- 30. CAVE FUTURE REALITYLAB (NYU) • Mirage Solo VR • •
- 31. (Google) • 16 GoProHero4 1 1000 • “Welcome to Light Fields” VR Google
- 32. NVIDIA Holodeck • NVIDIAVR • • NASA
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- 34. QualisysVR Solution (QUALISYS) • • SDK REST API Unity Unreal • 180fps 300fps 10,000fps
- 35. MixedReality Capture Studio(Microsoft) • MR Microsoft • 106 • IR
- 36. Virtual Light Booth(X-Rite) • • • • 4 3
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- 38. • • (03) ComputationalPhotography • (06)Virtually Human • (08) Computational Photos andVideos • (09) Interaction/VR • (10) Image & Shape Analysis With CNNs • (20) 3D Capture • (23) Computational Cameras
- 39. • • (03) ComputationalPhotography • (06)Virtually Human • (08) Computational Photos andVideos • (09) Interaction/VR • (10) Image & Shape Analysis With CNNs • (20) 3D Capture • (23) Computational Cameras
- 40. Exposure:A White-Box PhotoPost-Processing Framework (Microsoft, MIT) • Deep Learning • Deep Learning • GAN+
- 41. Deep Examplar-Based Colorization( , , Microsoft) • Deep Learning • Reference Reference • Reference
- 42. • • (03) ComputationalPhotography • (06)Virtually Human • (08) Computational Photos andVideos • (09) Interaction/VR • (10) Image & Shape Analysis With CNNs • (20) 3D Capture • (23) Computational Cameras
- 43. Deep Learning ofBiomimetic Sensorimotor Control for Biomechanical Human Animation (UCLA) • Deep Learning • 20 DNN • 2 8 216 2 29 39 2 DNN
- 44. • • (03) ComputationalPhotography • (06)Virtually Human • (08) Computational Photos andVideos • (09) Interaction/VR • (10) Image & Shape Analysis With CNNs • (20) 3D Capture • (23) Computational Cameras
- 45. Synthetic Depth-of-Field witha Single-Camera Mobile Phone (Google) • Google • depth map • Flickr 122k • 5.4MP 4
- 46. Stereo Magnification: LearningViewSynthesis Using Multiplane Images (UCBerkeley, Google) • • Youtube
- 47. Gigapixel PanoramaVideo Loops( , Microsoft) • • 58,699x20,497
- 48. An OmnistereoscopicVideo Pipelinefor Capture and Display of Real-WorldVR (Disney, KAIST) • 16 VR 360° • Monoscopic Stereoscopic • AR
- 49. • • (03) ComputationalPhotography • (06)Virtually Human • (08) Computational Photos andVideos • (09) Interaction/VR • (10) Image & Shape Analysis With CNNs • (20) 3D Capture • (23) Computational Cameras
- 50. In the Blinkof an Eye Leveraging Blink-Induced Suppression for Imperceptible Position and Orientation Redirection inVirtual Reality (Hamburg , Muenster , Central Florida ) • VR (e.g. Redirected walking) • VR
- 51. TowardsVirtual Reality InfiniteWalking Dynamic Saccadic Redirection (Stony Brook , NVIDIA, ,Adobe) • VR • • GPU
- 52. FaceVR Real-Time FacialReenactment and Eye Gaze Control inVirtual Reality (Erlangen-Nuremberg , MPI Informatics, Stanford ) • RGB-D IR VR
- 53. Deep Appearance Modelsfor Face Rendering (CMU) • Deep Learning • Mesh
- 54. • • (03) ComputationalPhotography • (06)Virtually Human • (08) Computational Photos andVideos • (09) Interaction/VR • (10) Image & Shape Analysis With CNNs • (20) 3D Capture • (23) Computational Cameras
- 55. Neural Best-Buddies SparseCross-Domain Correspondence (Tel Aviv , Microsoft, Hebrew , ) • • CNN feature map
- 56. • • (03) ComputationalPhotography • (06)Virtually Human • (08) Computational Photos andVideos • (09) Interaction/VR • (10) Image & Shape Analysis With CNNs • (20) 3D Capture • (23) Computational Cameras
- 57. Space-timeTomography for ContinuouslyDeforming Objects (KAUST) • CT
- 58. Instant 3D Photography(Facebook) • 3D
- 59. Reconstructing Scenes withMirror and Glass Surfaces (Facebook) •
- 60. Full 3D ReconstructionofTransparent Objects ( , Newfoundland Memorial ) •
- 61. • • (03) ComputationalPhotography • (06)Virtually Human • (08) Computational Photos andVideos • (09) Interaction/VR • (10) Image & Shape Analysis With CNNs • (20) 3D Capture • (23) Computational Cameras
- 62. Single-Photon 3D Imagingwith Deep Sensor Fusion (Stanford )
- 63. End-to-end Optimization ofOptics and Image Processing for Achromatic Extended Depth of Field and Super-resolution Imaging (Stanford , KAUST)
- 64. Megapixel Adaptive OpticsTowardsCorrecting Large-scale Distortions in Computational Cameras (KAUST)