[{"data":1,"prerenderedAt":955},["ShallowReactive",2],{"method-imap2021":3},{"method":4,"reference":55,"equipment":76,"figures":89,"results":90},{"id":5,"label":6,"shortName":7,"title":8,"year":9,"era":10,"cluster":11,"scope":12,"keyIdeaZh":13,"keyIdeaEn":14,"fulltextStatus":15,"publicationStatus":16,"recommendation":17,"constructionRelevance":18,"validationEnvironment":19,"strengths":23,"limitations":27,"sensors":34,"platform":36,"estimator":38,"association":39,"timeModel":40,"deskew":41,"loopClosure":42,"globalOptimization":43,"mapRepresentation":44,"prior":45,"outputGeometry":46,"compute":47,"codeUrl":48,"codeLicense":49,"relatedVersions":50},"imap2021","Sucar et al., 2021","iMAP","iMAP: Implicit Mapping and Positioning in Real-Time",2021,"recent","C09","odometry_with_local_mapping","iMAP 首次以單一 MLP 作為即時 RGB-D SLAM 的唯一地圖表示，追蹤執行緒對固定網路最佳化目前位姿，建圖執行緒同時最佳化網路與關鍵影格位姿。以資訊導向的像素取樣與關鍵影格重播緩解遺忘。作者強調 MLP 能對未觀測區域做平滑且合理的補洞，這對工程量測而言代表部分幾何並非量測所得。","First real-time RGB-D SLAM using a single MLP as the only map, trained live with keyframe replay and active pixel sampling.","full_text_reviewed","peer_reviewed_published","background","論文未涉及營建場域；僅 Replica、TUM 與手持 Kinect 自錄場景。",[20,21,22],"simulation","public_benchmark","controlled_experiment",[24,25,26],"Fills unobserved regions plausibly; average completion ratio 79.06% vs 75.09% for TSDF fusion on eight Replica scenes, 11% higher on office-3 (Sec. 4.2, Table 1)","About 60 times less memory than 256^3 TSDF fusion at similar accuracy (Sec. 4.2, Table 2)","Better than TSDF fusion where the depth camera fails, such as black, reflective or transparent surfaces (Sec. 4.2, Figs. 6, 8)",[28,29,30,31,32,33],"Mesh extraction is outside the SLAM loop (Sec. 4.1)","Follow-up [niceslam2022] attributes over-smoothing and poor scalability to the single-MLP design (NICE-SLAM abstract)","(inference) Hole filling produces geometry not supported by measurements, which must be flagged for engineering use","Average reconstruction accuracy on Replica is worse than TSDF fusion (4.43 cm vs 3.45 cm) (Table 1)","TUM ATE RMSE of 2.0 to 5.8 cm, worse than BAD-SLAM and ORB-SLAM2 on all three sequences and worse than Kintinuous on two (better on fr2\u002Fxyz, 2.0 vs 2.9 cm) (Sec. 4.3, Table 3)","Table 1 reports each scene at its highest reached completion ratio with the accuracy and completion at that point (Table 1 caption)",[35],"RGB-D (hand-held Microsoft Azure Kinect for real recordings; rendered Replica RGB-D sequences; TUM RGB-D sequences)",[37],"handheld","Adam gradient descent: pose-only tracking against a frozen MLP; mapping jointly optimizes MLP weights and keyframe poses","direct photometric (L1) + depth-variance-normalized geometric rendering losses on actively sampled pixels","discrete poses","not_applicable","none","joint optimization over a bounded keyframe window (no loop closure)","single MLP with Fourier-feature embedding (occupancy + colour)","none (trained live from scratch)","mesh by marching cubes on queried occupancy (for visualization\u002Fevaluation only, not part of SLAM)","Python and PyTorch with multi-processing on a single desktop CPU and GPU (models not reported); default tracking 101 ms (6 iterations) and joint optimisation 448 ms (10 iterations) running concurrently on the same GPU, giving about 10 Hz tracking and 2 Hz mapping; 1.04 MB MLP (width 256) vs 67.10 MB for 256^3 TSDF fusion",null,"not_verified",[51],{"relation":52,"title":53,"doi_or_url":54},"preprint","arXiv:2103.12352","https:\u002F\u002Farxiv.org\u002Fabs\u002F2103.12352",{"id":5,"kind":56,"shortName":7,"title":8,"authors":57,"year":9,"venue":62,"venueType":63,"publisher":64,"volumeIssuePages":65,"doi":66,"arxivId":67,"url":68,"firstPublicDate":69,"publicationStatus":16,"metadataStatus":70,"fulltextStatus":15,"era":10,"classicReason":41,"codeUrl":48,"cluster":11,"topics":71,"mdpi":72,"verification":73,"label":6,"fulltextRoute":74,"versionRead":75,"addedByCensus":72},"method",[58,59,60,61],"Edgar Sucar","Shikun Liu","Joseph Ortiz","Andrew J. Davison","2021 IEEE\u002FCVF International Conference on Computer Vision (ICCV)","conference","IEEE","pp. 6209-6218","10.1109\u002Ficcv48922.2021.00617","2103.12352","https:\u002F\u002Fapi.crossref.org\u002Fworks\u002F10.1109\u002Ficcv48922.2021.00617","2021-03-23","metadata_verified",[11],false,"confirmed","publisher OA","ICCV 2021 CVF Open Access version (identical to the accepted version except the watermark; CVF pagination 6229-6236, whereas Crossref lists pp. 6209-6218)",[77,83],{"category":78,"model":79,"canonical":79,"role":80,"dataset":48,"specs":81,"locator":82},"rgbd","Microsoft Azure Kinect","method input","hand-held RGB-D camera; frames processed at 10 Hz in the experiments","Fig. 1; Sec. 4.1",{"category":84,"model":85,"canonical":85,"role":86,"dataset":48,"specs":87,"locator":88},"compute","single desktop CPU and GPU (models not reported)","compute for runtime","PyTorch; tracking and mapping run concurrently on the same GPU","Sec. 1; Table 4",[],{"totalRows":91,"groupCount":92,"groups":93,"others":815},229,33,[94,260,436,684],{"slug":95,"group":96,"sourceId":5,"sourceLabel":6,"table":97,"selfRows":98,"metrics":99,"seqs":110,"entrants":131,"cells":136,"outcomes":254,"locators":255,"hardware":256,"wordings":257,"notes":258},"imap2021-table-1","imap2021:Table 1","Table 1",27,[100,104,106],{"label":101,"unit":102,"statistic":103,"alignment":42},"Acc. [cm]","cm","mean",{"label":105,"unit":102,"statistic":103,"alignment":42},"Comp. [cm]",{"label":107,"unit":108,"statistic":109,"alignment":42},"Comp. Ratio [\u003C 5cm %]","%","not_reported",[111,115,117,119,121,123,125,127,129],{"dataset":112,"sequence":113,"environment":114},"Replica","room-0","synthetic render of real indoor scan (Replica), 2000 RGB-D frames",{"dataset":112,"sequence":116,"environment":114},"room-1",{"dataset":112,"sequence":118,"environment":114},"room-2",{"dataset":112,"sequence":120,"environment":114},"office-0",{"dataset":112,"sequence":122,"environment":114},"office-1",{"dataset":112,"sequence":124,"environment":114},"office-2",{"dataset":112,"sequence":126,"environment":114},"office-3",{"dataset":112,"sequence":128,"environment":114},"office-4",{"dataset":112,"sequence":130,"environment":114},"Avg.",[132,134],{"name":7,"methodId":5,"linkable":133,"proposed":133,"self":133},true,{"name":135,"methodId":48,"linkable":72,"proposed":72,"self":72},"TSDF Fusion (with iMAP tracking)",[137,141,144,147,149,151,153,155,157,159,162,164,166,169,171,173,176,178,180,183,185,187,190,192,194,197,199,201,203,205,207,209,211,213,215,217,219,221,223,225,227,229,231,232,234,236,238,240,242,244,246,248,250,252],[138,138,138,139,140,138,140,140,138],0,3.58,-1,[138,142,138,143,140,138,140,140,138],1,5.06,[138,145,138,146,140,138,140,140,138],2,83.91,[138,138,142,148,140,138,140,140,138],3.69,[138,142,142,150,140,138,140,140,138],4.87,[138,145,142,152,140,138,140,140,138],83.45,[138,138,145,154,140,138,140,140,138],4.68,[138,142,145,156,140,138,140,140,138],5.51,[138,145,145,158,140,138,140,140,138],75.53,[138,138,160,161,140,138,140,140,138],3,5.87,[138,142,160,163,140,138,140,140,138],6.11,[138,145,160,165,140,138,140,140,138],77.71,[138,138,167,168,140,138,140,140,138],4,3.71,[138,142,167,170,140,138,140,140,138],5.26,[138,145,167,172,140,138,140,140,138],79.64,[138,138,174,175,140,138,140,140,138],5,4.81,[138,142,174,177,140,138,140,140,138],5.65,[138,145,174,179,140,138,140,140,138],77.22,[138,138,181,182,140,138,140,140,138],6,4.27,[138,142,181,184,140,138,140,140,138],5.45,[138,145,181,186,140,138,140,140,138],77.34,[138,138,188,189,140,138,140,140,138],7,4.83,[138,142,188,191,140,138,140,140,138],6.59,[138,145,188,193,140,138,140,140,138],77.63,[138,138,195,196,140,138,140,140,138],8,4.43,[138,142,195,198,140,138,140,140,138],5.56,[138,145,195,200,140,138,140,140,138],79.06,[142,138,138,202,140,138,140,140,138],4.21,[142,142,138,204,140,138,140,140,138],5.04,[142,145,138,206,140,138,140,140,138],76.9,[142,138,142,208,140,138,140,140,138],3.08,[142,142,142,210,140,138,140,140,138],4.35,[142,145,142,212,140,138,140,140,138],79.87,[142,138,145,214,140,138,140,140,138],2.88,[142,142,145,216,140,138,140,140,138],5.4,[142,145,145,218,140,138,140,140,138],77.79,[142,138,160,220,140,138,140,140,138],2.7,[142,142,160,222,140,138,140,140,138],10.47,[142,145,160,224,140,138,140,140,138],79.6,[142,138,167,226,140,138,140,140,138],2.66,[142,142,167,228,140,138,140,140,138],10.29,[142,145,167,230,140,138,140,140,138],71.93,[142,138,174,182,140,138,140,140,138],[142,142,174,233,140,138,140,140,138],6.43,[142,145,174,235,140,138,140,140,138],71.66,[142,138,181,237,140,138,140,140,138],4.07,[142,142,181,239,140,138,140,140,138],6.26,[142,145,181,241,140,138,140,140,138],65.87,[142,138,188,243,140,138,140,140,138],3.7,[142,142,188,245,140,138,140,140,138],4.78,[142,145,188,247,140,138,140,140,138],77.11,[142,138,195,249,140,138,140,140,138],3.45,[142,142,195,251,140,138,140,140,138],6.63,[142,145,195,253,140,138,140,140,138],75.09,[],[97],[],[],[259],"Replica reconstruction from 200,000 points sampled on GT and reconstructed meshes; each scene reported at its highest reached completion ratio with the accuracy and completion at that point; TSDF fusion [4,17] uses iMAP camera tracking; meshes by marching cubes for evaluation only",{"slug":261,"group":262,"sourceId":263,"sourceLabel":264,"table":265,"selfRows":98,"metrics":266,"seqs":271,"entrants":291,"cells":299,"outcomes":430,"locators":431,"hardware":432,"wordings":433,"notes":434},"voxfusion2022-table-2","voxfusion2022:Table 2","voxfusion2022","Yang et al., 2022","Table 2",[267,268,269],{"label":101,"unit":102,"statistic":103,"alignment":41},{"label":105,"unit":102,"statistic":103,"alignment":41},{"label":270,"unit":108,"statistic":41,"alignment":41},"Comp. 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]","niceslam2022",{"name":298,"methodId":48,"linkable":72,"proposed":133,"self":72},"Ours",[300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,329,331,333,334,336,338,340,341,343,345,347,349,351,353,355,357,359,360,362,364,366,368,370,372,374,376,378,380,382,384,386,388,390,392,394,396,398,399,401,403,405,407,409,410,412,414,416,418,420,422,424,426,428],[138,138,138,139,140,138,140,140,138],[138,138,142,148,140,138,140,140,138],[138,138,145,154,140,138,140,140,138],[138,138,160,161,140,138,140,140,138],[138,138,167,168,140,138,140,140,138],[138,138,174,175,140,138,140,140,138],[138,138,181,182,140,138,140,140,138],[138,138,188,189,140,138,140,140,138],[138,138,195,196,140,138,140,140,138],[138,142,138,143,140,138,140,140,138],[138,142,142,150,140,138,140,140,138],[138,142,145,156,140,138,140,140,138],[138,142,160,163,140,138,140,140,138],[138,142,167,170,140,138,140,140,138],[138,142,174,177,140,138,140,140,138],[138,142,181,184,140,138,140,140,138],[138,142,188,191,140,138,140,140,138],[138,142,195,198,140,138,140,140,138],[138,145,138,146,140,138,140,140,138],[138,145,142,152,140,138,140,140,138],[138,145,145,158,140,138,140,140,138],[138,145,160,165,140,138,140,140,138],[138,145,167,172,140,138,140,140,138],[138,145,174,179,140,138,140,140,138],[138,145,181,186,140,138,140,140,138],[138,145,188,193,140,138,140,140,138],[138,145,195,200,140,138,140,140,138],[142,138,138,328,140,138,140,140,138],3.53,[142,138,142,330,140,138,140,140,138],3.6,[142,138,145,332,140,138,140,140,138],3.03,[142,138,160,198,140,138,140,140,138],[142,138,167,335,140,138,140,140,138],3.35,[142,138,174,337,140,138,140,140,138],4.71,[142,138,181,339,140,138,140,140,138],3.84,[142,138,188,335,140,138,140,140,138],[142,138,195,342,140,138,140,140,138],3.87,[142,142,138,344,140,138,140,140,138],3.4,[142,142,142,346,140,138,140,140,138],3.62,[142,142,145,348,140,138,140,140,138],3.27,[142,142,160,350,140,138,140,140,138],4.55,[142,142,167,352,140,138,140,140,138],4.03,[142,142,174,354,140,138,140,140,138],3.94,[142,142,181,356,140,138,140,140,138],3.99,[142,142,188,358,140,138,140,140,138],4.15,[142,142,195,342,140,138,140,140,138],[142,145,138,361,140,138,140,140,138],86.05,[142,145,142,363,140,138,140,140,138],80.75,[142,145,145,365,140,138,140,140,138],87.23,[142,145,160,367,140,138,140,140,138],79.34,[142,145,167,369,140,138,140,140,138],82.13,[142,145,174,371,140,138,140,140,138],80.35,[142,145,181,373,140,138,140,140,138],80.55,[142,145,188,375,140,138,140,140,138],82.88,[142,145,195,377,140,138,140,140,138],82.41,[145,138,138,379,140,138,140,140,138],2.41,[145,138,142,381,140,138,140,140,138],1.62,[145,138,145,383,140,138,140,140,138],3.11,[145,138,160,385,140,138,140,140,138],1.74,[145,138,167,387,140,138,140,140,138],1.69,[145,138,174,389,140,138,140,140,138],2.23,[145,138,181,391,140,138,140,140,138],2.84,[145,138,188,393,140,138,140,140,138],3.31,[145,138,195,395,140,138,140,140,138],2.37,[145,142,138,397,140,138,140,140,138],2.6,[145,142,142,389,140,138,140,140,138],[145,142,145,400,140,138,140,140,138],1.93,[145,142,160,402,140,138,140,140,138],1.39,[145,142,167,404,140,138,140,140,138],1.8,[145,142,174,406,140,138,140,140,138],2.71,[145,142,181,408,140,138,140,140,138],2.69,[145,142,188,214,140,138,140,140,138],[145,142,195,411,140,138,140,140,138],2.28,[145,145,138,413,140,138,140,140,138],92.87,[145,145,142,415,140,138,140,140,138],93.48,[145,145,145,417,140,138,140,140,138],94.34,[145,145,160,419,140,138,140,140,138],97.21,[145,145,167,421,140,138,140,140,138],93.76,[145,145,174,423,140,138,140,140,138],90.98,[145,145,181,425,140,138,140,140,138],90.73,[145,145,188,427,140,138,140,140,138],89.48,[145,145,195,429,140,138,140,140,138],92.86,[],[265],[],[],[435],"Replica 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