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.

1. SIGGRAPH2018
(COMPUTERVISION, CAMERA,VR )
TOSHIKITSUBOI

2. SIGGRAPH
• Special Interests Group on Computer GRAPHics
• Association for Computing Machinery( :ACM) CG
• 1974
• ( )
• 160 16,637

3. SIGGRAPH
ART GALLERY
ART PAPERS
BIRDS OF 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 WebVR API2.0 NYU CAVE etc.
‣ (EmergingTech.)
‣ GPU (NVIDIA RTX )
‣ VR
‣ Google Microsoft
‣

7. EMERGINGTECHNOLOGIES

8. EMERGINGTECHNOLOGIES
•
•
• CSL
•
•
•
•
•

9. Tastes Controller ( , )
• GTS: Galvanic Tongue
Stimulation
•
• VR/AR

10. Human Support Robot ( TRI)
• ROS
•

11. HEADLIGHT;Wearable Projector (Sony CSL)
•
• 105° 55°

12. 2400fps ( )
• (400fps )
(2400fps)
•

13. Realtime Non-Line-Of-Site Imaging (Stanford )
•
SPAD Time Of Flight
• LiDAR

14. Transcalibur ( )
• VR

15. Make your own Retinal 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

19. Fusion ( )
•
• HMD

20. (Lightform Inc.)
•
•

21. Spherical FishTankVR Display (British Columbia Saskatchewan )
•
•

22. Steerable Application-Adaptive Near-Eye Displays (NVIDIA, UNC)
•
AR HMD
• Norland Products
Norland Optical Adhesives
• EmergingTechnologies Best
in Show

23. SEER (Stimulative Emotional Expression Robot)
•
• TakayukiTodo

24. IMMERSIVE PAVILION

25. Microsoft Hololens
1 2
3 4

26. VR
Stereoscope
(1838 )
Nintendo
3D Glasses
(1987 )
SegaScope
3D Glasses
(1988 )
Nintendo
Power Glove
(1989 )

27. VR
Virtual Research
HMD
(1991 )
Takara HMD
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 )
Avegant Glyph
(2016 )
Google
Cardboard
(2014 )

30. CAVE FUTURE REALITY LAB (NYU)
• Mirage Solo
VR
•
•

31. (Google)
• 16 GoPro Hero4
1
1000
• “Welcome to Light Fields”
VR Google

32. NVIDIA Holodeck
• NVIDIA VR
•
• NASA

33. EXHIBITION

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

37. TECHNICAL PAPERS

38. •
• (03) Computational Photography
• (06)Virtually Human
• (08) Computational Photos andVideos
• (09) Interaction/VR
• (10) Image & Shape Analysis With CNNs
• (20) 3D Capture
• (23) Computational Cameras

39. •
• (03) Computational Photography
• (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 Photo Post-Processing Framework (Microsoft, MIT)
• Deep Learning
• Deep Learning
• GAN+

41. Deep Examplar-Based Colorization ( , , Microsoft)
• Deep Learning
•
Reference
Reference
• Reference

42. •
• (03) Computational Photography
• (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 of Biomimetic Sensorimotor Control for Biomechanical Human
Animation (UCLA)
• Deep Learning
• 20 DNN
• 2 8 216
2 29 39
2 DNN

44. •
• (03) Computational Photography
• (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 with a Single-Camera Mobile Phone (Google)
• Google
•
depth map
• Flickr 122k
• 5.4MP 4

46. Stereo Magnification: LearningView Synthesis Using Multiplane Images
(UCBerkeley, Google)
•
• Youtube

47. Gigapixel PanoramaVideo Loops ( , Microsoft)
•
• 58,699x20,497

48. An OmnistereoscopicVideo Pipeline for Capture and Display of Real-WorldVR
(Disney, KAIST)
• 16 VR
360°
• Monoscopic
Stereoscopic
• AR

49. •
• (03) Computational Photography
• (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 Blink of 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 Infinite Walking Dynamic Saccadic Redirection (Stony
Brook , NVIDIA, ,Adobe)
• VR
•
• GPU

52. FaceVR Real-Time Facial Reenactment and Eye Gaze Control inVirtual Reality
(Erlangen-Nuremberg , MPI Informatics, Stanford )
• RGB-D IR
VR

53. Deep Appearance Models for Face Rendering (CMU)
•
Deep Learning
•
Mesh

54. •
• (03) Computational Photography
• (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 Sparse Cross-Domain Correspondence (Tel Aviv , Microsoft, Hebrew ,
)
•
• CNN feature map

56. •
• (03) Computational Photography
• (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 Continuously Deforming Objects (KAUST)
• CT

58. Instant 3D Photography (Facebook)
•
3D

59. Reconstructing Scenes with Mirror and Glass Surfaces (Facebook)
•

60. Full 3D Reconstruction ofTransparent Objects ( , Newfoundland Memorial )
•

61. •
• (03) Computational Photography
• (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 Imaging with Deep Sensor Fusion (Stanford )

63. End-to-end Optimization of Optics and Image Processing for Achromatic
Extended Depth of Field and Super-resolution Imaging (Stanford , KAUST)

64. Megapixel Adaptive OpticsTowards Correcting Large-scale Distortions in
Computational Cameras (KAUST)