http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114758337-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_0dfb38da0444a9ff5250a10d408277cb |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-253 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V20-64 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-82 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-80 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V40-16 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-22 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-40 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-774 |
| filingDate | 2022-06-16^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_2e825e607721f5432b2d1f08754b1356 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_bcecd7f2a4671b974e5e0d9a5291effc http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7226d0807665d6436226710c137a391b http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_64b38be814c2e3e1acc90062241adb45 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_33b888605fc5226085aeb05babe48613 |
| publicationDate | 2022-07-15^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-114758337-A |
| titleOfInvention | A semantic instance reconstruction method, apparatus, device and medium |
| abstract | The present application discloses a semantic instance reconstruction method, device, device and medium, which relate to the field of three-dimensional vision, including: using a first target detection network to process an original image of a target scene to obtain first feature information of a target object, and using a first target detection network to process an original image of a target scene The second target detection network processes the 3D point cloud of the target scene to obtain the second feature information of the target object; predicts the first rough point cloud of the target object based on the first feature information, and predicts the first rough point cloud of the target object based on the first feature information and the second feature information Predict the three-dimensional detection result of the target object, and obtain the second rough point cloud of the target object based on the three-dimensional detection result; obtain the initial point cloud of the target object based on the first rough point cloud and the second rough point cloud, and use a preset shape to generate a network The initial point cloud is processed to obtain the semantic instance reconstruction result of the target object. By combining the first feature information of the original image and the second feature information of the 3D point cloud, the quality of the semantic instance reconstruction result can be improved. |
| priorityDate | 2022-06-16^^<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/SID419563789 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID6438639 |
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