[{"data":1,"prerenderedAt":728},["ShallowReactive",2],{"method-dust3r2024":3},{"method":4,"reference":49,"equipment":71,"figures":79,"results":80},{"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":21,"limitations":26,"sensors":31,"platform":33,"estimator":34,"association":35,"timeModel":36,"deskew":36,"loopClosure":36,"globalOptimization":37,"mapRepresentation":38,"prior":39,"outputGeometry":40,"compute":41,"codeUrl":42,"codeLicense":43,"relatedVersions":44},"dust3r2024","Wang et al., 2024","DUSt3R","DUSt3R: Geometric 3D Vision Made Easy",2024,"recent","C09","map_representation_or_reconstruction","DUSt3R 將雙視角三維重建改寫為以 Transformer 直接回歸兩張影像在同一座標系下的逐像素點圖（pointmap），不需要相機內參或位姿；多張影像時以全域對齊合併點圖。訓練時以平均距離正規化點圖，因此輸出沒有公制尺度。作者在 DTU 零樣本測試指出其以回歸取得的幾何精度低於使用真值相機並做三角化的 MVS 方法。","Regresses scale-normalized pairwise pointmaps from uncalibrated images with a Transformer, unifying depth, pose and matching; multi-view via global alignment.","full_text_reviewed","peer_reviewed_published","background","論文未涉及營建場域。",[20],"public_benchmark",[22,23,24,25],"Works without camera calibration or poses (abstract)","Zero-shot DTU accuracy 2.677 mm, completeness 0.805 mm, overall 1.741 mm (Table 4; 512 model, no GT cameras)","Multi-view pose on CO3Dv2 with global alignment: RRA@15 96.2, RTA@15 86.8, mAA(30) 76.7 versus PoseDiffusion 80.5, 79.8 and 66.5 (Table 2 right)","Multi-view depth average rel 4.73 and inlier ratio 64.52 without GT poses, ranges or intrinsics (Table 3)",[27,28,29,30],"Does not reach the accuracy of MVS methods that use GT poses and DTU training; regression less accurate than sub-pixel triangulation (Sec. 4.5)","Pointmaps are regressed up to an unknown scale and no geometric constraint is enforced, so they need not follow a physically plausible camera model (Sec. 3.1); multi-view depth evaluation needs median scaling to ground truth (Sec. 4.4)","DTU numbers require aligning the predictions to the ground-truth coordinate system (Sec. 4.5)","With unknown query focal length, median localization errors on Cambridge Landmarks reach 64 to 245 cm because sparse ground-truth pointmaps prevent reliable scaling (App. E, Table 6)",[32],"monocular camera (unposed, uncalibrated images)",[],"feed-forward Transformer pointmap regression for image pairs; global alignment (not reprojection BA) for >2 views","implicit (regressed pointmaps in a common frame; matches recoverable from pointmaps)","not_applicable","global alignment of pairwise pointmaps over a connectivity graph: per-pair rigid pose and scale plus per-view pointmaps optimized by gradient descent on confidence-weighted 3D distances (not reprojection errors), product of pair scales fixed to 1; can be parameterized with pinhole cameras to recover poses, intrinsics and depthmaps","per-pixel pointmaps with confidence","learned 3D prior from 8.5M image pairs of eight datasets (Habitat, ARKitScenes, MegaDepth, Static Scenes 3D, BlendedMVS, ScanNet++, CO3Dv2, Waymo), initialized from CroCo v2 pretraining; ViT-Large encoder, ViT-Base decoder, DPT head","dense point clouds, depth maps, relative\u002Fabsolute camera poses and intrinsics (scale-normalized)","pairwise network inference about 40 ms per image pair on an H100 GPU; global alignment by gradient descent converges in a few hundred steps, seconds on a standard GPU; multi-view depth 0.13 s (Table 3)","https:\u002F\u002Fgithub.com\u002Fnaver\u002Fdust3r","CC BY-NC-SA 4.0",[45],{"relation":46,"title":47,"doi_or_url":48},"preprint","arXiv:2312.14132","https:\u002F\u002Farxiv.org\u002Fabs\u002F2312.14132",{"id":5,"kind":50,"shortName":7,"title":8,"authors":51,"year":9,"venue":57,"venueType":58,"publisher":59,"volumeIssuePages":60,"doi":61,"arxivId":62,"url":63,"firstPublicDate":64,"publicationStatus":16,"metadataStatus":65,"fulltextStatus":15,"era":10,"classicReason":36,"codeUrl":42,"cluster":11,"topics":66,"mdpi":67,"verification":68,"label":6,"fulltextRoute":69,"versionRead":70,"addedByCensus":67},"component",[52,53,54,55,56],"Shuzhe Wang","Vincent Leroy","Yohann Cabon","Boris Chidlovskii","Jerome Revaud","2024 IEEE\u002FCVF Conference on Computer Vision and Pattern Recognition (CVPR)","conference","IEEE","pp. 20697-20709","10.1109\u002Fcvpr52733.2024.01956","2312.14132","https:\u002F\u002Fapi.crossref.org\u002Fworks\u002F10.1109\u002Fcvpr52733.2024.01956","2023-12-21","metadata_verified",[11],false,"confirmed","arXiv","arXiv v3 (2312.14132v3, 2 Dec 2024; v3 fixes a dataset reference) including appendices B to F; CVPR 2024 version of record not compared",[72],{"category":73,"model":74,"canonical":74,"role":75,"dataset":76,"specs":77,"locator":78},"compute","H100 GPU","compute for runtime",null,"pairwise inference about 40 ms","Sec. 3.4",[],{"totalRows":81,"groupCount":82,"groups":83,"others":687},72,12,[84,315,386,479],{"slug":85,"group":86,"sourceId":87,"sourceLabel":88,"table":89,"selfRows":90,"metrics":91,"seqs":101,"entrants":122,"cells":135,"outcomes":304,"locators":309,"hardware":310,"wordings":312,"notes":313},"slam3r2025-table-1","slam3r2025:Table 1","slam3r2025","Liu et al., 2025","Table 1",17,[92,97,99],{"label":93,"unit":94,"statistic":95,"alignment":96},"Acc.","cm","mean","other: Umeyama similarity alignment followed by ICP to the ground-truth point cloud",{"label":98,"unit":94,"statistic":95,"alignment":96},"Comp.",{"label":100,"unit":100,"statistic":95,"alignment":36},"FPS",[102,106,108,110,112,114,116,118,120],{"dataset":103,"sequence":104,"environment":105},"7-Scenes","Chess","real indoor rooms",{"dataset":103,"sequence":107,"environment":105},"Fire",{"dataset":103,"sequence":109,"environment":105},"Heads",{"dataset":103,"sequence":111,"environment":105},"Office",{"dataset":103,"sequence":113,"environment":105},"Pumpkin",{"dataset":103,"sequence":115,"environment":105},"RedKitchen",{"dataset":103,"sequence":117,"environment":105},"Stairs",{"dataset":103,"sequence":119,"environment":105},"average of test sequences",{"dataset":103,"sequence":121,"environment":105},"all test sequences",[123,126,129,131,133],{"name":124,"methodId":5,"linkable":125,"proposed":67,"self":125},"DUSt3R [ 64 ]",true,{"name":127,"methodId":128,"linkable":125,"proposed":67,"self":67},"MASt3R [ 28 ]","mast3r2024",{"name":130,"methodId":76,"linkable":67,"proposed":67,"self":67},"Spann3R [ 61 ]",{"name":132,"methodId":76,"linkable":67,"proposed":125,"self":67},"SLAM3R-NoConf (Ours)",{"name":134,"methodId":76,"linkable":67,"proposed":125,"self":67},"SLAM3R (Ours)",[136,140,143,145,147,150,152,155,157,160,162,165,167,170,172,175,177,179,181,183,185,187,189,190,192,194,196,198,200,201,202,204,206,208,209,211,213,215,217,219,220,222,224,226,228,230,232,234,236,238,240,241,242,244,246,248,249,251,253,255,257,259,261,263,265,267,269,271,273,275,277,279,281,283,285,287,288,290,292,294,296,298,300,301,303],[137,137,137,138,139,137,139,139,137],0,2.26,-1,[137,141,137,142,139,137,139,139,137],1,2.13,[137,137,141,144,139,137,139,139,137],1.04,[137,141,141,146,139,137,139,139,137],1.5,[137,137,148,149,139,137,139,139,137],2,1.66,[137,141,148,151,139,137,139,139,137],0.98,[137,137,153,154,139,137,139,139,137],3,4.62,[137,141,153,156,139,137,139,139,137],4.74,[137,137,158,159,139,137,139,139,137],4,1.73,[137,141,158,161,139,137,139,139,137],2.43,[137,137,163,164,139,137,139,139,137],5,1.95,[137,141,163,166,139,137,139,139,137],2.36,[137,137,168,169,139,137,139,139,137],6,3.37,[137,141,168,171,139,137,139,139,137],10.75,[137,137,173,174,139,137,139,139,137],7,2.19,[137,141,173,176,139,137,139,139,137],3.24,[137,148,178,76,137,137,137,139,137],8,[141,137,137,180,139,137,139,139,137],2.08,[141,141,137,182,139,137,139,139,137],2.12,[141,137,141,184,139,137,139,139,137],1.54,[141,141,141,186,139,137,139,139,137],1.43,[141,137,148,188,139,137,139,139,137],1.06,[141,141,148,144,139,137,139,139,137],[141,137,153,191,139,137,139,139,137],3.23,[141,141,153,193,139,137,139,139,137],3.19,[141,137,158,195,139,137,139,139,137],5.68,[141,141,158,197,139,137,139,139,137],3.07,[141,137,163,199,139,137,139,139,137],3.5,[141,141,163,169,139,137,139,139,137],[141,137,168,166,139,137,139,139,137],[141,141,168,203,139,137,139,139,137],13.16,[141,137,173,205,139,137,139,139,137],3.04,[141,141,173,207,139,137,139,139,137],3.9,[141,148,178,76,141,137,137,139,137],[148,137,137,210,139,137,139,139,137],2.23,[148,141,137,212,139,137,139,139,137],1.68,[148,137,141,214,139,137,139,139,137],0.88,[148,141,141,216,139,137,139,139,137],0.92,[148,137,148,218,139,137,139,139,137],2.67,[148,141,148,151,139,137,139,139,137],[148,137,153,221,139,137,139,139,137],5.86,[148,141,153,223,139,137,139,139,137],3.54,[148,137,158,225,139,137,139,139,137],2.25,[148,141,158,227,139,137,139,139,137],1.85,[148,137,163,229,139,137,139,139,137],2.68,[148,141,163,231,139,137,139,139,137],1.8,[148,137,168,233,139,137,139,139,137],5.65,[148,141,168,235,139,137,139,139,137],5.15,[148,137,173,237,139,137,139,139,137],3.42,[148,141,173,239,139,137,139,139,137],2.41,[148,148,178,76,148,137,137,139,137],[153,137,137,182,139,137,139,139,137],[153,141,137,243,139,137,139,139,137],1.21,[153,137,141,245,139,137,139,139,137],0.95,[153,141,141,247,139,137,139,139,137],0.8,[153,137,148,191,139,137,139,139,137],[153,141,148,250,139,137,139,139,137],1.67,[153,137,153,252,139,137,139,139,137],2.59,[153,141,153,254,139,137,139,139,137],2.21,[153,137,158,256,139,137,139,139,137],1.99,[153,141,158,258,139,137,139,139,137],2.04,[153,137,163,260,139,137,139,139,137],2.09,[153,141,163,262,139,137,139,139,137],1.88,[153,137,168,264,139,137,139,139,137],4.54,[153,141,168,266,139,137,139,139,137],6.38,[153,137,173,268,139,137,139,139,137],2.4,[153,141,173,270,139,137,139,139,137],2.24,[153,148,178,272,153,137,137,139,137],25,[158,137,137,274,139,137,139,139,137],1.63,[158,141,137,276,139,137,139,139,137],1.31,[158,137,141,278,139,137,139,139,137],0.84,[158,141,141,280,139,137,139,139,137],0.83,[158,137,148,282,139,137,139,139,137],2.95,[158,141,148,284,139,137,139,139,137],1.22,[158,137,153,286,139,137,139,139,137],2.32,[158,141,153,138,139,137,139,139,137],[158,137,158,289,139,137,139,139,137],1.81,[158,141,158,291,139,137,139,139,137],2.05,[158,137,163,293,139,137,139,139,137],1.84,[158,141,163,295,139,137,139,139,137],1.94,[158,137,168,297,139,137,139,139,137],4.19,[158,141,168,299,139,137,139,139,137],6.91,[158,137,173,142,139,137,139,139,137],[158,141,173,302,139,137,139,139,137],2.34,[158,148,178,272,153,137,137,139,137],[305,306,307,308],"other: as written '\u003C 1'","other: as written '\u003C\u003C 1'","other: as written '> 50'","other: approximate, as written '~25'",[89],[311],"single NVIDIA 4090D GPU (Sec. 4.1)",[],[314],"7 Scenes, one-twentieth of frames of each test sequence as input video; accuracy and completeness in cm against back-projected ground-truth depth; SLAM3R filters points with confidence threshold 3, SLAM3R-NoConf keeps all",{"slug":316,"group":317,"sourceId":5,"sourceLabel":6,"table":318,"selfRows":319,"metrics":320,"seqs":330,"entrants":349,"cells":352,"outcomes":379,"locators":380,"hardware":381,"wordings":382,"notes":383},"dust3r2024-table-3","dust3r2024:Table 3","Table 3",13,[321,325,327],{"label":322,"unit":323,"statistic":324,"alignment":324},"rel (absolute relative error)","not_stated","not_reported",{"label":326,"unit":323,"statistic":324,"alignment":324},"tau (inlier ratio, threshold 1.03)",{"label":328,"unit":329,"statistic":324,"alignment":36},"time (s)","s",[331,335,337,339,341,343,345],{"dataset":332,"sequence":333,"environment":334},"KITTI","test set","mixed indoor and outdoor",{"dataset":336,"sequence":333,"environment":334},"ScanNet",{"dataset":338,"sequence":333,"environment":334},"ETH3D",{"dataset":340,"sequence":333,"environment":334},"DTU",{"dataset":342,"sequence":333,"environment":334},"T&T",{"dataset":344,"sequence":333,"environment":334},"Average",{"dataset":346,"sequence":347,"environment":348},"all Table 3 test sets","time column of Table 3 (unit of work not stated)","mixed",[350],{"name":351,"methodId":5,"linkable":125,"proposed":125,"self":125},"DUSt3R 512 (no GT pose, range or intrinsics; median alignment)",[353,355,357,359,361,363,365,367,369,371,373,375,377],[137,137,137,354,139,137,139,139,137],9.11,[137,141,137,356,139,137,139,139,137],39.49,[137,137,141,358,139,137,139,139,137],4.93,[137,141,141,360,139,137,139,139,137],60.2,[137,137,148,362,139,137,139,139,137],2.91,[137,141,148,364,139,137,139,139,137],76.91,[137,137,153,366,139,137,139,139,137],3.52,[137,141,153,368,139,137,139,139,137],69.33,[137,137,158,370,139,137,139,139,137],3.17,[137,141,158,372,139,137,139,139,137],76.68,[137,137,163,374,139,137,139,139,137],4.73,[137,141,163,376,139,137,139,139,137],64.52,[137,148,168,378,139,137,139,139,141],0.13,[],[318],[],[],[384,385],"Multi-view depth; rel is absolute relative error and tau the inlier ratio at 1.03; DUSt3R ScanNet value in parentheses (same-domain training via Habitat)","Multi-view depth timing",{"slug":387,"group":388,"sourceId":5,"sourceLabel":6,"table":389,"selfRows":178,"metrics":390,"seqs":397,"entrants":404,"cells":419,"outcomes":472,"locators":474,"hardware":475,"wordings":476,"notes":477},"dust3r2024-table-2-right","dust3r2024:Table 2 (right)","Table 2 (right)",[391,393,395],{"label":392,"unit":323,"statistic":324,"alignment":36},"RRA@15 (relative rotation accuracy)",{"label":394,"unit":323,"statistic":324,"alignment":36},"RTA@15 (relative translation accuracy)",{"label":396,"unit":323,"statistic":324,"alignment":36},"mAA(30)",[398,402],{"dataset":399,"sequence":400,"environment":401},"CO3Dv2","10 random frames per sequence","object-centric (CO3Dv2) or indoor\u002Foutdoor video (RealEstate10K)",{"dataset":403,"sequence":400,"environment":401},"RealEstate10K",[405,407,409,411,413,415,417],{"name":406,"methodId":76,"linkable":67,"proposed":67,"self":67},"RelPose",{"name":408,"methodId":76,"linkable":67,"proposed":67,"self":67},"Colmap+SPSG",{"name":410,"methodId":76,"linkable":67,"proposed":67,"self":67},"PixSfM",{"name":412,"methodId":76,"linkable":67,"proposed":67,"self":67},"PosReg",{"name":414,"methodId":76,"linkable":67,"proposed":67,"self":67},"PoseDiffusion (RealEstate10K result from CO3Dv2-trained model)",{"name":416,"methodId":5,"linkable":125,"proposed":125,"self":125},"DUSt3R 512 (w\u002F PnP)",{"name":418,"methodId":5,"linkable":125,"proposed":125,"self":125},"DUSt3R 512 (w\u002F GA)",[420,422,423,424,425,427,429,431,433,435,437,439,441,443,445,447,448,450,452,454,456,458,460,462,464,466,468,470],[137,137,137,421,139,137,139,139,137],57.1,[137,141,137,76,137,137,139,139,137],[137,148,137,76,137,137,139,139,137],[137,148,141,76,137,137,139,139,137],[141,137,137,426,139,137,139,139,137],36.1,[141,141,137,428,139,137,139,139,137],27.3,[141,148,137,430,139,137,139,139,137],25.3,[141,148,141,432,139,137,139,139,137],45.2,[148,137,137,434,139,137,139,139,137],33.7,[148,141,137,436,139,137,139,139,137],32.9,[148,148,137,438,139,137,139,139,137],30.1,[148,148,141,440,139,137,139,139,137],49.4,[153,137,137,442,139,137,139,139,137],53.2,[153,141,137,444,139,137,139,139,137],49.1,[153,148,137,446,139,137,139,139,137],45,[153,148,141,76,137,137,139,139,137],[158,137,137,449,139,137,139,139,137],80.5,[158,141,137,451,139,137,139,139,137],79.8,[158,148,137,453,139,137,139,139,137],66.5,[158,148,141,455,139,137,139,139,137],48,[163,137,137,457,139,137,139,139,137],94.3,[163,141,137,459,139,137,139,139,137],88.4,[163,148,137,461,139,137,139,139,137],77.2,[163,148,141,463,139,137,139,139,137],61.2,[168,137,137,465,139,137,139,139,137],96.2,[168,141,137,467,139,137,139,139,137],86.8,[168,148,137,469,139,137,139,139,137],76.7,[168,148,141,471,139,137,139,139,137],67.7,[473],"not_reported (dash in table)",[389],[],[],[478],"Multi-view relative pose with 10 random frames per sequence (45 pairs); DUSt3R not trained on RealEstate10K",{"slug":480,"group":481,"sourceId":128,"sourceLabel":482,"table":483,"selfRows":173,"metrics":484,"seqs":506,"entrants":511,"cells":534,"outcomes":680,"locators":681,"hardware":683,"wordings":684,"notes":685},"mast3r2024-table-2","mast3r2024:Table 2","Leroy et al., 2024","Table 2",[485,489,492,495,499,502,504],{"label":486,"unit":487,"statistic":324,"alignment":488},"VCRE Reproj.","px","none",{"label":490,"unit":491,"statistic":324,"alignment":488},"VCRE Prec. (\u003C 90 px)","%",{"label":493,"unit":494,"statistic":324,"alignment":488},"VCRE AUC (\u003C 90 px)","ratio",{"label":496,"unit":497,"statistic":498,"alignment":488},"Pose Median Err. (translation)","m","median",{"label":500,"unit":501,"statistic":498,"alignment":488},"Pose Median Err. (rotation)","deg",{"label":503,"unit":491,"statistic":324,"alignment":488},"Pose Precision (\u003C 25 cm, 5 deg)",{"label":505,"unit":494,"statistic":324,"alignment":488},"Pose AUC (\u003C 25 cm, 5 deg)",[507],{"dataset":508,"sequence":509,"environment":510},"Map-free relocalization","test set (130 scenes)","Map-free relocalization test set (130 scenes, each with two video sequences); metric relative pose from a single reference image; qualitative pairs with viewpoint changes up to 180 deg",[512,514,516,518,520,522,524,526,528,530,532],{"name":513,"methodId":76,"linkable":67,"proposed":67,"self":67},"RPR [5] (DPT depth)",{"name":515,"methodId":76,"linkable":67,"proposed":67,"self":67},"SIFT [54] (DPT depth)",{"name":517,"methodId":76,"linkable":67,"proposed":67,"self":67},"SP+SG [78] (DPT depth)",{"name":519,"methodId":76,"linkable":67,"proposed":67,"self":67},"LoFTR [87] (KBR depth)",{"name":521,"methodId":76,"linkable":67,"proposed":67,"self":67},"FAR [75] (auto)",{"name":523,"methodId":76,"linkable":67,"proposed":67,"self":67},"RoMa [29] (DPT depth)",{"name":525,"methodId":76,"linkable":67,"proposed":67,"self":67},"Mickey [8] (auto)",{"name":527,"methodId":5,"linkable":125,"proposed":67,"self":125},"DUSt3R [106] (DPT depth)",{"name":529,"methodId":128,"linkable":125,"proposed":125,"self":67},"MASt3R (DPT depth)",{"name":531,"methodId":128,"linkable":125,"proposed":125,"self":67},"MASt3R (auto, own metric depth)",{"name":533,"methodId":128,"linkable":125,"proposed":125,"self":67},"MASt3R (direct reg., PnP on pointmap)",[535,537,539,541,542,544,545,547,549,550,552,554,556,558,560,562,563,565,566,568,570,572,574,576,578,579,581,583,585,587,589,591,593,595,597,599,601,603,605,607,609,611,613,615,617,619,620,621,623,625,627,629,631,633,635,637,639,641,643,645,646,648,650,652,655,657,659,661,662,664,666,668,670,672,674,676,678],[137,137,137,536,139,137,139,139,137],147.1,[137,141,137,538,139,137,139,139,137],40.2,[137,148,137,540,139,137,139,139,137],0.402,[137,153,137,212,139,137,139,139,137],[137,158,137,543,139,137,139,139,137],22.5,[137,163,137,168,139,137,139,139,137],[137,168,137,546,139,137,139,139,137],0.06,[141,137,137,548,139,137,139,139,137],222.8,[141,141,137,272,139,137,139,139,137],[141,148,137,551,139,137,139,139,137],0.504,[141,153,137,553,139,137,139,139,137],2.93,[141,158,137,555,139,137,139,139,137],61.4,[141,163,137,557,139,137,139,139,137],10.3,[141,168,137,559,139,137,139,139,137],0.252,[148,137,137,561,139,137,139,139,137],160.3,[148,141,137,426,139,137,139,139,137],[148,148,137,564,139,137,139,139,137],0.602,[148,153,137,262,139,137,139,139,137],[148,158,137,567,139,137,139,139,137],25.4,[148,163,137,569,139,137,139,139,137],16.8,[148,168,137,571,139,137,139,139,137],0.346,[153,137,137,573,139,137,139,139,137],165,[153,141,137,575,139,137,139,139,137],34.3,[153,148,137,577,139,137,139,139,137],0.634,[153,153,137,210,139,137,139,139,137],[153,158,137,580,139,137,139,139,137],37.8,[153,163,137,582,139,137,139,139,137],11,[153,168,137,584,139,137,139,139,137],0.295,[158,137,137,586,139,137,139,139,137],137,[158,141,137,588,139,137,139,139,137],44.2,[158,148,137,590,139,137,139,139,137],0.68,[158,153,137,592,139,137,139,139,137],1.48,[158,158,137,594,139,137,139,139,137],17.2,[158,163,137,596,139,137,139,139,137],17.7,[158,168,137,598,139,137,139,139,137],0.392,[163,137,137,600,139,137,139,139,137],128.8,[163,141,137,602,139,137,139,139,137],45.6,[163,148,137,604,139,137,139,139,137],0.669,[163,153,137,606,139,137,139,139,137],1.23,[163,158,137,608,139,137,139,139,137],11.1,[163,163,137,610,139,137,139,139,137],22.8,[163,168,137,612,139,137,139,139,137],0.407,[168,137,137,614,139,137,139,139,137],129.5,[168,141,137,616,139,137,139,139,137],49.3,[168,148,137,618,139,137,139,139,137],0.748,[168,153,137,149,139,137,139,139,137],[168,158,137,428,139,137,139,139,137],[168,163,137,622,139,137,139,139,137],13.3,[168,168,137,624,139,137,139,139,137],0.325,[173,137,137,626,139,137,139,139,137],116,[173,141,137,628,139,137,139,139,137],50.3,[173,148,137,630,139,137,139,139,137],0.697,[173,153,137,632,139,137,139,139,137],0.97,[173,158,137,634,139,137,139,139,137],7.1,[173,163,137,636,139,137,139,139,137],21.6,[173,168,137,638,139,137,139,139,137],0.394,[178,137,137,640,139,137,139,139,137],104,[178,141,137,642,139,137,139,139,137],54.2,[178,148,137,644,139,137,139,139,137],0.726,[178,153,137,247,139,137,139,139,137],[178,158,137,647,139,137,139,139,137],2.2,[178,163,137,649,139,137,139,139,137],27,[178,168,137,651,139,137,139,139,137],0.456,[653,137,137,654,139,137,139,139,137],9,48.7,[653,141,137,656,139,137,139,139,137],79.3,[653,148,137,658,139,137,139,139,137],0.933,[653,153,137,660,139,137,139,139,137],0.36,[653,158,137,647,139,137,139,139,137],[653,163,137,663,139,137,139,139,137],54.7,[653,168,137,665,139,137,139,139,137],0.74,[667,137,137,442,139,137,139,139,137],10,[667,141,137,669,139,137,139,139,137],79.1,[667,148,137,671,139,137,139,139,137],0.941,[667,153,137,673,139,137,139,139,137],0.42,[667,158,137,675,139,137,139,139,137],3.1,[667,163,137,677,139,137,139,139,137],53,[667,168,137,679,139,137,139,139,137],0.777,[],[682],"Table 2 (VoR)",[],[],[686],"Map-free relocalization test set (VoR table, which adds FAR, RoMa and Mickey compared with arXiv v1). VCRE = virtual correspondence reprojection error, precision and AUC at VCRE \u003C 90 px; pose precision and AUC at \u003C 25 cm and 5 deg; median translation and rotation error; the depth column gives the metric-scale source (DPT fine-tuned on KITTI, KBR, or MASt3R's own depth, 'auto').",[688,694,699,704,709,714,720,724],{"group":689,"slug":690,"sourceLabel":88,"table":691,"selfRows":168,"datasets":692},"slam3r2025:Supp. Table 8","slam3r2025-supp-table-8","Supp. Table 8",[338,336,693],"Tanks and Temples",{"group":695,"slug":696,"sourceLabel":697,"table":318,"selfRows":158,"datasets":698},"vggt2025:Table 3","vggt2025-table-3","Wang et al., 2025b",[338],{"group":700,"slug":701,"sourceLabel":6,"table":702,"selfRows":153,"datasets":703},"dust3r2024:Table 4","dust3r2024-table-4","Table 4",[340],{"group":705,"slug":706,"sourceLabel":482,"table":707,"selfRows":153,"datasets":708},"mast3r2024:Table 3 right","mast3r2024-table-3-right","Table 3 right",[340],{"group":710,"slug":711,"sourceLabel":88,"table":483,"selfRows":153,"datasets":712},"slam3r2025:Table 2","slam3r2025-table-2",[713],"Replica",{"group":715,"slug":716,"sourceLabel":697,"table":89,"selfRows":153,"datasets":717},"vggt2025:Table 1","vggt2025-table-1",[399,718,719],"RealEstate10K (unseen)","RealEstate10K and CO3Dv2 (single time column)",{"group":721,"slug":722,"sourceLabel":697,"table":483,"selfRows":153,"datasets":723},"vggt2025:Table 2","vggt2025-table-2",[340],{"group":725,"slug":726,"sourceLabel":88,"table":318,"selfRows":148,"datasets":727},"slam3r2025:Table 3","slam3r2025-table-3",[103,713],1790510664793]