Schedule at a Glance
T: Tutorial W: Workshop D: Demo O: Oral P: Poster GC: Grand Challenges
| Monday, July 5; Beijing (UTC +8) | |||||||
| 9:00 | W1: Quality of Experience in Interactive Multimedia | T1:Screen Content Coding in Recently Developed Video Coding Standards | T6: Next Generation Fingerprint: from Searching 2 Billion Images to Revocable Biometrics | ||||
| 9:30 | |||||||
| 10:00 | |||||||
| 10:30 | |||||||
| 11:00 | |||||||
| 11:30 | |||||||
| 12:00 | |||||||
| 12:30 | |||||||
| 13:00 | |||||||
| 13:30 | |||||||
| 14:00 | W3: Hyper-Realistic Multimedia for Enhanced Quality of Experience | T3:Versatile Video Coding – Open Optimized Implementations | T4:Internet of Things (IoT), From Sensors to Cloud | ||||
| 14:30 | |||||||
| 15:00 | |||||||
| 15:30 | |||||||
| 16:00 | |||||||
| 16:30 | |||||||
| 17:00 | |||||||
| Tuesday, July 6; Beijing (UTC +8) | |||||||
| 9:00 | Opening Ceremony | ||||||
| 9:30 | |||||||
| 10:00 | O1: Image/Video Enhancement I | O2: Cross-modal and multi-modal multimedia analysis | O3: Emerging applications of artificial intelligence | O4: Multimedia databases and data mining | O5: Speech/audio synthesis and coding | O6: Special Session: Deep Learning for Multimedia Applications with Limited Supervision | GC1: Few-Shot Learning for vehicle footprint recognition | 
| 10:30 | |||||||
| 11:00 | |||||||
| 11:30 | P1: Image/Video Enhancement I | O7: Multimedia activity analysis and understanding | P2: Object/Person detection, Tracking and Recognition I | P3: Emerging applications of artificial intelligence I | P4: Multimedia databases and data mining | P5: Special Session: Advancd Video Coding and Deep Active Learning | |
| 12:00 | |||||||
| 12:30 | |||||||
| 13:00 | |||||||
| 13:30 | |||||||
| 14:00 | O8: Image/Video Enhancement II | O9: Multimedia representation learning | O10: 3D stereo computing | O11: Multimedia for society and health | O12: Special Session: Advancd Video Coding and Deep Active Learning | O13: Emerging multimedia applications | |
| 14:30 | |||||||
| 15:00 | Multimedia Rising Star Competition | ||||||
| 15:30 | P6: Image/Video Enhancement II | O14: Multimedia semantic segmentation | P7: Object/Person detection, Tracking and Recognition II | P8: Emerging multimedia applications of deep learning | P9: Multimedia for society and health | P10: Special Session: Advanced Representation Learning and Depth-Related Processing | |
| 16:00 | |||||||
| 16:30 | |||||||
| 20:00 | Best Paper Session | ||||||
| Wednesday, July 7; Beijing (UTC +8) | |||||||
| 9:00 | Keynote Speech 1 | ||||||
| 9:30 | |||||||
| 10:00 | O15: Image/Video Synthesis and Creation I | O16: Object/Person detection, Tracking and Recognition I | O17: Emerging multimedia applications of deep learning I | O18: Multimedia security, privacy and forensic I | O19: Special Session: Advanced Representation Learning for Robust Multimedia Image Understanding | O20: Multimedia Applications I | GC2: Challenge on Quality Assessment of Compressed UGC Videos | 
| 10:30 | |||||||
| 11:00 | |||||||
| 11:30 | P11: Image/Video Enhancement III | O21: Object/Person detection, Tracking and Recognition II | P12: Multimedia analysis and understanding I | P13: Emerging applications of artificial intelligence II | P14: Multimedia security, privacy and forensics I | P15: Speial Session: Multimedia Processing | |
| 12:00 | |||||||
| 12:30 | |||||||
| 13:00 | |||||||
| 13:30 | |||||||
| 14:00 | O22: Image/Video Synthesis and Creation II | O23: Multimedia analysis and understanding I | O24: Multimedia interaction & Multimedia quality assessment | O25: Multimedia security, privacy and forensic II | O26: Special Session: Recent Advance in Depth-Related Processing and Applications | P16: Multimedia analysis and processing | GC3: The 3rd Grand Challenges of 106-Point Facial Landmark Localization | 
| 14:30 | |||||||
| 15:00 | |||||||
| 15:30 | P17: Image/Video Enhancement IV | P18: Object/Person detection, Tracking and Recognition III | P19: Multimedia analysis and understanding II | P20: Immersive media | P21: Multimedia security, privacy and forensics II | P22: Multimedia Applications I | |
| 16:00 | |||||||
| 16:30 | |||||||
| Thursday, July 8; Beijing (UTC +8) | |||||||
| 9:00 | Keynote Speech 2 | ||||||
| 9:30 | |||||||
| 10:00 | O27: Image/Video Enhancement III | O28: Multimedia analysis and understanding II | O29: Emerging multimedia applications of deep learning II | O30: Multimedia Applications II | O31: Special Session: Multimedia Knowledge-Driven Deep Analysis and Forensics/Security | O32: Industry and Application Track I | Open Source Competition | 
| 10:30 | |||||||
| 11:00 | |||||||
| 11:30 | P23: Image/video synthesis and creation | P24: Cross-modal and multi-modal media analysis I | P25: Multimedia activity analysis and understanding | P26: Emerging multimedia applications and technologies | P27: Multimedia Applications II | P28: Special Session: Deep Learning for Multimedia Applications with Limited Supervision | |
| 12:00 | |||||||
| 12:30 | |||||||
| 13:00 | |||||||
| 13:30 | |||||||
| 14:00 | O33: Image/video acquisition and compression | O34: Multimedia analysis and understanding III | P29: Multimedia representation learning | P30: Speech/audio synthesis and coding | O35: Special Session: Advances in Language, Vision, and Limited Supervision | O36: Industry and Application Track II | D1 | 
| 14:30 | |||||||
| 15:00 | |||||||
| 15:30 | P31: Image/video acquisition, compression, and procesing | P32: Cross-modal and multi-modal media analysis II | P33: Multimedia semantic segmentation | P34: Multimedia interaction & Multimedia quality assessment | D2 | D3 | D4 | 
| 16:00 | |||||||
| 16:30 | |||||||
| 18:00 | Awards and Closing Ceremony | ||||||
| Friday, July 9; Beijing (UTC +8) | |||||||
| 9:00 | T5:Effective Medical Image Analysis Models with Efficient Annotations | T2:Visual Backbone Network Design | |||||
| 9:30 | |||||||
| 10:00 | |||||||
| 10:30 | |||||||
| 11:00 | |||||||
| 11:30 | |||||||
| 12:00 | |||||||
| 12:30 | |||||||
| 13:00 | |||||||
| 13:30 | |||||||
| 14:00 | W2: Artificial Intelligence in Sports (AI-Sports) | W4: Big Surveillance Data Analysis and Processing (BIG-Surv) | T7: Adversarial Examples for Deep Learning: Attack, Defense and Robustness | T8: Person Re-Identification: Recent Advances and Challenges | |||
| 14:30 | |||||||
| 15:00 | |||||||
| 15:30 | |||||||
| 16:00 | |||||||
| 16:30 | |||||||
| 17:00 | |||||||
 
 
 
 
