[{"data":1,"prerenderedAt":721},["ShallowReactive",2],{"method-photoslam2024":3},{"method":4,"reference":57,"equipment":78,"figures":106,"results":107},{"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":26,"sensors":32,"platform":36,"estimator":40,"association":41,"timeModel":42,"deskew":43,"loopClosure":44,"globalOptimization":45,"mapRepresentation":46,"prior":47,"outputGeometry":48,"compute":49,"codeUrl":50,"codeLicense":51,"relatedVersions":52},"photoslam2024","Huang et al., 2024c","Photo-SLAM","Photo-SLAM: Real-Time Simultaneous Localization and Photorealistic Mapping for Monocular, Stereo, and RGB-D Cameras",2024,"recent","C09","full_slam_with_global_correction","Photo-SLAM 將 ORB-SLAM3 的特徵式定位、局部光束調整與迴圈閉合，與以高斯參數擴充的「超基元」地圖解耦結合，幾何由特徵點與因子圖負責，外觀由高斯潑濺負責。作者明言目標是沉浸式探索的精簡表示而非稠密網格，網格重建評估不在範圍內。","Decouples ORB-SLAM3 geometry (with loop closure) from a Gaussian-based photorealistic map; dense mesh reconstruction is out of scope.","full_text_reviewed","peer_reviewed_published","background","論文未涉及營建場域；資料為 Replica、TUM RGB-D、EuRoC 與 ZED 2 戶外自錄。",[20,21,22],"simulation","public_benchmark","controlled_experiment",[24,25],"Real-time on embedded Jetson AGX Orin (Sec. 4.1; Sec. 5)","Loop closure reduces ghosting in the photorealistic map (Sec. 3.5)",[27,28,29,30,31],"Mesh reconstruction evaluation out of scope (Sec. 4.1)","(inference) Dense geometry is not measured, so engineering use would rely on sparse ORB points","Peak tracking time occurs when a loop closure is detected and drift is corrected (Supp. Sec. 6, Fig. 12)","Outdoor ZED 2 results are qualitative only (Fig. 9)","(derived from Table 2) with RGB-D input on TUM fr1-desk the ATE RMSE is 2.603 cm against 1.724 cm for ORB-SLAM3",[33,34,35],"monocular camera","stereo camera (EuRoC MAV dataset; hand-held ZED 2 outdoors)","RGB-D",[37,38,39],"simulation (Replica)","UAV (EuRoC MAV dataset)","handheld (ZED 2 stereo camera, outdoor, qualitative only)","ORB-SLAM3-based factor graph (Levenberg-Marquardt) localization and local BA; SGD for photorealistic mapping","ORB feature correspondences (geometry); photometric loss (appearance)","discrete poses","not_applicable","ORB-SLAM3-style loop closure; keyframes and hyper primitives corrected by a similarity transformation","loop-closure correction of keyframes and primitives","hyper primitives: ORB map points extended with Gaussian parameters","none","sparse ORB points + Gaussians and renderings; mesh reconstruction explicitly out of scope (Sec. 4.1)","all methods run on a desktop with an NVIDIA RTX 4090 24 GB GPU, Intel Core i9-13900K CPU and 64 GB RAM; Photo-SLAM also run on a laptop (NVIDIA RTX 3080 Ti 16 GB Laptop GPU, Intel Core i9-12900HX, 32 GB RAM) and a Jetson AGX Orin Developer Kit (Sec. 4.1); on Replica, tracking at about 42 FPS on the desktop and about 18 FPS on the Jetson with 4 to 6 GB GPU memory (Table 1)","https:\u002F\u002Fgithub.com\u002FHuajianUP\u002FPhoto-SLAM","GPL-3.0",[53],{"relation":54,"title":55,"doi_or_url":56},"preprint","arXiv:2311.16728","https:\u002F\u002Farxiv.org\u002Fabs\u002F2311.16728",{"id":5,"kind":58,"shortName":7,"title":8,"authors":59,"year":9,"venue":64,"venueType":65,"publisher":66,"volumeIssuePages":67,"doi":68,"arxivId":69,"url":70,"firstPublicDate":71,"publicationStatus":16,"metadataStatus":72,"fulltextStatus":15,"era":10,"classicReason":43,"codeUrl":50,"cluster":11,"topics":73,"mdpi":74,"verification":75,"label":6,"fulltextRoute":76,"versionRead":77,"addedByCensus":74},"method",[60,61,62,63],"Huajian Huang","Longwei Li","Hui Cheng","Sai-Kit Yeung","2024 IEEE\u002FCVF Conference on Computer Vision and Pattern Recognition (CVPR)","conference","IEEE","pp. 21584-21593","10.1109\u002Fcvpr52733.2024.02039","2311.16728","https:\u002F\u002Fapi.crossref.org\u002Fworks\u002F10.1109\u002Fcvpr52733.2024.02039","2023-11-28","metadata_verified",[11],false,"confirmed","arXiv","arXiv v2 (2024-04-08) read in full including supplementary Sec. 6 to 8 and Tables 5 to 8; CVF open-access CVPR 2024 version also read: Tables 1 to 3 and the hardware paragraph identical to arXiv v2",[79,86,93,96,99,102],{"category":80,"model":81,"canonical":81,"role":82,"dataset":83,"specs":84,"locator":85},"stereo_camera","ZED 2","method input",null,"hand-held stereo camera used to collect outdoor unbounded scenes","Sec. 4.1; Sec. 4.2 On Stereo; Fig. 9",{"category":87,"model":88,"canonical":89,"role":90,"dataset":83,"specs":91,"locator":92},"compute","NVIDIA RTX 4090 24 GB","NVIDIA RTX 4090 24GB","compute for runtime","desktop GPU with Intel Core i9-13900K and 64 GB RAM; used for Photo-SLAM and all baselines","Sec. 4.1",{"category":87,"model":94,"canonical":94,"role":90,"dataset":83,"specs":95,"locator":92},"Intel Core i9-13900K","desktop CPU, 64 GB RAM",{"category":87,"model":97,"canonical":97,"role":90,"dataset":83,"specs":98,"locator":92},"NVIDIA RTX 3080ti 16 GB Laptop GPU","laptop with Intel Core i9-12900HX and 32 GB RAM",{"category":87,"model":100,"canonical":100,"role":90,"dataset":83,"specs":101,"locator":92},"Intel Core i9-12900HX","laptop CPU, 32 GB RAM",{"category":87,"model":103,"canonical":103,"role":90,"dataset":83,"specs":104,"locator":105},"NVIDIA Jetson AGX Orin Developer Kit","embedded platform; about 18 tracking FPS and about 100 rendering FPS on Replica","Sec. 4.1; Table 1; Supp. Fig. 11",[],{"totalRows":108,"groupCount":109,"groups":110,"others":698},76,8,[111,336,466,536],{"slug":112,"group":113,"sourceId":5,"sourceLabel":6,"table":114,"selfRows":115,"metrics":116,"seqs":132,"entrants":139,"cells":174,"outcomes":327,"locators":329,"hardware":330,"wordings":333,"notes":334},"photoslam2024-table-1","photoslam2024:Table 1","Table 1",24,[117,122,125,129],{"label":118,"unit":119,"statistic":120,"alignment":121},"Localization RMSE (cm) of ATE","cm","RMSE","not_reported",{"label":123,"unit":119,"statistic":124,"alignment":121},"Localization STD (cm) of ATE","std",{"label":126,"unit":127,"statistic":128,"alignment":43},"Tracking FPS","Hz","mean",{"label":130,"unit":131,"statistic":121,"alignment":43},"GPU Memory Usage","GB",[133,137],{"dataset":134,"sequence":135,"environment":136},"Replica","average over Replica sequences, Mono input","synthetic indoor rooms and offices",{"dataset":134,"sequence":138,"environment":136},"average over Replica sequences, RGB-D 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[27]","pointslam2023",[175,179,182,185,187,189,191,193,195,197,199,201,203,204,205,207,209,212,214,216,218,221,223,225,226,228,230,232,233,236,238,240,241,243,245,247,248,250,252,254,255,257,259,261,262,265,267,269,270,272,274,276,277,280,282,284,286,288,290,292,293,295,297,299,300,302,304,306,307,309,311,313,314,316,317,319,320,322,324,326],[176,176,176,177,178,176,178,178,176],0,3.942,-1,[176,180,176,181,178,176,178,178,176],1,3.115,[176,183,176,184,178,176,176,178,176],2,58.749,[176,186,176,176,178,176,176,178,176],3,[180,176,176,188,178,176,178,178,176],0.725,[180,180,176,190,178,176,178,178,176],0.308,[180,183,176,192,178,176,176,178,176],35.473,[180,186,176,194,178,176,176,178,176],11,[183,176,176,196,178,176,178,178,176],99.9415,[183,180,176,198,178,176,178,178,176],35.336,[183,183,176,200,178,176,176,178,176],2.384,[183,186,176,202,178,176,176,178,176],12,[186,176,176,83,176,176,178,178,176],[186,180,176,83,176,176,178,178,176],[186,183,176,206,178,176,176,178,176],49.2,[186,186,176,208,178,176,176,178,176],6,[210,176,176,211,178,176,178,178,176],4,71.054,[210,180,176,213,178,176,178,178,176],24.593,[210,183,176,215,178,176,176,178,176],25.366,[210,186,176,217,178,176,176,178,176],22,[219,176,176,220,178,176,178,178,176],5,1.235,[219,180,176,222,178,176,178,178,176],0.756,[219,183,176,224,178,176,180,178,176],18.315,[219,186,176,210,178,176,180,178,176],[208,176,176,227,178,176,178,178,176],0.713,[208,180,176,229,178,176,178,178,176],0.524,[208,183,176,231,178,176,183,178,176],19.974,[208,186,176,210,178,176,183,178,176],[234,176,176,235,178,176,178,178,176],7,1.091,[234,180,176,237,178,176,178,178,176],0.892,[234,183,176,239,178,176,176,178,176],41.646,[234,186,176,208,178,176,176,178,176],[176,176,180,242,178,176,178,178,176],1.833,[176,180,180,244,178,176,178,178,176],1.478,[176,183,180,246,178,176,176,178,176],52.209,[176,186,180,176,178,176,176,178,176],[180,176,180,249,178,176,178,178,176],0.634,[180,180,180,251,178,176,178,178,176],0.248,[180,183,180,253,178,176,176,178,176],36.452,[180,186,180,194,178,176,176,178,176],[109,176,180,256,178,176,178,178,176],1.606,[109,180,180,258,178,176,178,178,176],0.969,[109,183,180,260,178,176,176,178,176],8.63,[109,186,180,219,178,176,176,178,176],[263,176,180,264,178,176,178,178,176],9,2.35,[263,180,180,266,178,176,178,178,176],1.59,[263,183,180,268,178,176,176,178,176],2.331,[263,186,180,202,178,176,176,178,176],[186,176,180,271,178,176,178,178,176],0.888,[186,180,180,273,178,176,178,178,176],0.562,[186,183,180,275,178,176,176,178,176],41.333,[186,186,180,208,178,176,176,178,176],[278,176,180,279,178,176,178,178,176],10,0.568,[278,180,180,281,178,176,178,178,176],0.274,[278,183,180,283,178,176,176,178,176],6.687,[278,186,180,285,178,176,176,178,176],21,[194,176,180,287,178,176,178,178,176],1.158,[194,180,180,289,178,176,178,178,176],0.602,[194,183,180,291,178,176,176,178,176],14.575,[194,186,180,210,178,176,176,178,176],[210,176,180,294,178,176,178,178,176],0.571,[210,180,180,296,178,176,178,178,176],0.218,[210,183,180,298,178,176,176,178,176],19.437,[210,186,180,115,178,176,176,178,176],[202,176,180,301,178,176,178,178,176],0.596,[202,180,180,303,178,176,178,178,176],0.249,[202,183,180,305,178,176,176,178,176],0.345,[202,186,180,115,178,176,176,178,176],[219,176,180,308,178,176,178,178,176],0.581,[219,180,180,310,178,176,178,178,176],0.289,[219,183,180,312,178,176,180,178,176],17.926,[219,186,180,210,178,176,180,178,176],[208,176,180,315,178,176,178,178,176],0.59,[208,180,180,310,178,176,178,178,176],[208,183,180,318,178,176,183,178,176],20.597,[208,186,180,210,178,176,183,178,176],[234,176,180,321,178,176,178,178,176],0.604,[234,180,180,323,178,176,178,178,176],0.298,[234,183,180,325,178,176,176,178,176],42.485,[234,186,180,219,178,176,176,178,176],[328],"failed ('-' in the localization columns; the Table 1 caption defines '-' as no view-rendering support or failure to track camera poses, and Orbeez-SLAM does render in this table)",[114],[331,103,332],"desktop: NVIDIA RTX 4090 24 GB + Intel Core i9-13900K + 64 GB RAM","laptop: NVIDIA RTX 3080 Ti 16 GB Laptop GPU + Intel Core i9-12900HX + 32 GB RAM",[],[335],"Replica, average of 5 runs per sequence; all baselines run with official code on the desktop; '-' means rendering not supported or tracking failed; rendering metrics (PSNR, SSIM, LPIPS), operation time and rendering FPS not extracted",{"slug":337,"group":338,"sourceId":5,"sourceLabel":6,"table":339,"selfRows":340,"metrics":341,"seqs":344,"entrants":359,"cells":369,"outcomes":460,"locators":461,"hardware":462,"wordings":463,"notes":464},"photoslam2024-table-2","photoslam2024:Table 2","Table 2",18,[342],{"label":343,"unit":119,"statistic":120,"alignment":121},"RMSE (cm)",[345,349,351,353,355,357],{"dataset":346,"sequence":347,"environment":348},"TUM RGB-D","fr1-desk (Mono input)","indoor office (real)",{"dataset":346,"sequence":350,"environment":348},"fr2-xyz (Mono input)",{"dataset":346,"sequence":352,"environment":348},"fr3-office (Mono input)",{"dataset":346,"sequence":354,"environment":348},"fr1-desk (RGB-D input)",{"dataset":346,"sequence":356,"environment":348},"fr2-xyz (RGB-D input)",{"dataset":346,"sequence":358,"environment":348},"fr3-office (RGB-D input)",[360,361,362,363,364,365,366,367,368],{"name":141,"methodId":142,"linkable":143,"proposed":74,"self":74},{"name":145,"methodId":146,"linkable":143,"proposed":74,"self":74},{"name":153,"methodId":83,"linkable":74,"proposed":74,"self":74},{"name":155,"methodId":5,"linkable":143,"proposed":143,"self":143},{"name":157,"methodId":5,"linkable":143,"proposed":143,"self":143},{"name":159,"methodId":5,"linkable":143,"proposed":143,"self":143},{"name":164,"methodId":149,"linkable":143,"proposed":74,"self":74},{"name":166,"methodId":167,"linkable":143,"proposed":74,"self":74},{"name":169,"methodId":170,"linkable":143,"proposed":74,"self":74},[370,372,374,376,378,380,382,384,386,388,390,392,394,396,398,400,402,404,406,408,410,412,414,416,418,420,422,424,426,428,430,432,434,436,438,440,442,444,446,448,450,452,454,456,458],[176,176,176,371,178,176,178,178,176],1.534,[176,176,180,373,178,176,178,178,176],0.72,[176,176,183,375,178,176,178,178,176],1.4,[180,176,176,377,178,176,178,178,176],78.245,[180,176,180,379,178,176,178,178,176],36.05,[180,176,183,381,178,176,178,178,176],154.383,[183,176,176,383,178,176,178,178,176],33.122,[183,176,180,385,178,176,178,178,176],28.584,[183,176,183,387,178,176,178,178,176],105.755,[186,176,176,389,178,176,176,178,176],1.757,[186,176,180,391,178,176,176,178,176],0.558,[186,176,183,393,178,176,176,178,176],1.687,[210,176,176,395,178,176,180,178,176],1.549,[210,176,180,397,178,176,180,178,176],0.852,[210,176,183,399,178,176,180,178,176],1.542,[219,176,176,401,178,176,183,178,176],1.539,[219,176,180,403,178,176,183,178,176],0.984,[219,176,183,405,178,176,183,178,176],1.257,[176,176,186,407,178,176,178,178,176],1.724,[176,176,210,409,178,176,178,178,176],0.385,[176,176,219,411,178,176,178,178,176],1.698,[180,176,186,413,178,176,178,178,176],91.985,[180,176,210,415,178,176,178,178,176],41.833,[180,176,219,417,178,176,178,178,176],160.141,[208,176,186,419,178,176,178,178,176],19.317,[208,176,210,421,178,176,178,178,176],36.103,[208,176,219,423,178,176,178,178,176],25.309,[234,176,186,425,178,176,178,178,176],3.359,[234,176,210,427,178,176,178,178,176],31.448,[234,176,219,429,178,176,178,178,176],25.808,[109,176,186,431,178,176,178,178,176],3.094,[109,176,210,433,178,176,178,178,176],31.347,[109,176,219,435,178,176,178,178,176],25.374,[183,176,186,437,178,176,178,178,176],2.119,[183,176,210,439,178,176,178,178,176],31.788,[183,176,219,441,178,176,178,178,176],26.802,[186,176,186,443,178,176,176,178,176],4.571,[186,176,210,445,178,176,176,178,176],0.36,[186,176,219,447,178,176,176,178,176],1.874,[210,176,186,449,178,176,180,178,176],1.891,[210,176,210,451,178,176,180,178,176],0.361,[210,176,219,453,178,176,180,178,176],1.315,[219,176,186,455,178,176,183,178,176],2.603,[219,176,210,457,178,176,183,178,176],0.346,[219,176,219,459,178,176,183,178,176],1.001,[],[339],[103,332,331],[],[465],"TUM RGB-D, ATE RMSE in cm, average of 5 runs; rendering metrics not extracted",{"slug":467,"group":468,"sourceId":5,"sourceLabel":6,"table":469,"selfRows":202,"metrics":470,"seqs":472,"entrants":483,"cells":489,"outcomes":530,"locators":531,"hardware":532,"wordings":533,"notes":534},"photoslam2024-table-3","photoslam2024:Table 3","Table 3",[471],{"label":343,"unit":119,"statistic":120,"alignment":121},[473,477,479,481],{"dataset":474,"sequence":475,"environment":476},"EuRoC MAV","MH-01","indoor sequences (Sec. 4.1 contrasts the benchmark datasets with the self-collected outdoor scenes); EuRoC MAV stereo input, scene type not further described in the 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