http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114494050-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_217f2be73fd6be0be36dd55803d3bec5 |
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10016 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T5-003 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T5-50 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T5-50 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T5-00 |
| filingDate | 2022-01-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_85375a9a9200d48202f9197e607d404c http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_27c7968b05868a845efc2dee6c48d064 |
| publicationDate | 2022-05-13-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-114494050-A |
| titleOfInvention | A Self-Supervised Video Deblurring and Image Interpolation Method Based on Event Camera |
| abstract | The invention provides a method for self-supervised video deblurring and image frame interpolation based on event camera, including the construction of blurred video and event stream data set, event stream preprocessing, construction of learnable double integral network and fusion network to process blurred video Network training with event streaming, self-supervised framework and reconstruction of high frame rate clear video. The preprocessing method of the event stream is established by combining the event generation model and the blurred image generation model, which ensures that the present invention can select any target moment inside or outside the exposure time of the blurred video for potentially clear image reconstruction. The preprocessed event stream and blurred images are fed into a learnable double integral network and fusion network for motion blur removal and image interpolation. Finally, using the relationship between the blurred video, clear video and event stream, a self-supervised framework is constructed to train the network model, and the trained model is used to process the blurred video and event stream to reconstruct a clear video with high frame rate. The invention solves the problems of motion blur and information loss between frames, and has better deblurring and image frame insertion effects. |
| priorityDate | 2022-01-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
| Predicate | Subject |
|---|---|
| isDiscussedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419559532 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID24404 |
Total number of triples: 23.