[{"data":1,"prerenderedAt":136},["ShallowReactive",2],{"run:materials-phase-i-adaptive-12500":3,"run-findings:materials-phase-i-adaptive-12500":110},{"run":4,"config":21,"metrics":55,"curve":61,"assets":109},{"id":5,"title":5,"subtitle":6,"eyebrow":7,"date":8,"workspace":9,"commit":10,"tags":11,"verdict":20},"materials-phase-i-adaptive-12500","Phase I scene-adaptive: materials @ stop_iter=12500 (fast converger 仮説検証) variant (early stop + SH progressive)","Run summary · P1 Phase G.5 final Pareto integration","2026-05-25","splat","6a5d86d",[12,13,14,15,16,17,18,19],"p1-g","phase-g","early-stop","sh-progressive","stacked","lego-15k","brush-compat","premultiplied","partial",[22,25,28,31,34,37,40,43,46,49,52],{"key":23,"value":24},"dataset","\u002FUsers\u002Fotkrickey\u002Fdev\u002F3dgs-workspace\u002Fdatasets\u002Fnerf_synthetic\u002Fmaterials",{"key":26,"value":27},"gt_convention","Premultiplied",{"key":29,"value":30},"iterations","12,500",{"key":32,"value":33},"seed","42",{"key":35,"value":36},"capacity","1,000,000 splats",{"key":38,"value":39},"sh_degree","3",{"key":41,"value":42},"loss","L1Ssim",{"key":44,"value":45},"lambda","0.200",{"key":47,"value":48},"ssim","window=7 sigma=1",{"key":50,"value":51},"backend.backward","Simd",{"key":53,"value":54},"backend.loss_path","Gpu",{"psnr":56,"wallclock":57,"wallclock_regress":58,"splats":59,"final_loss":60},29.97312355041504,"10m 59s",false,340763,"7.158034e-3",{"loss":62,"splats":93},{"iters":63,"values":78},[64,65,66,67,68,69,70,71,72,73,74,75,76,77],1,1000,2000,3000,4000,5000,6000,7000,8000,9000,10000,11000,12000,12500,[79,80,81,82,83,84,85,86,87,88,89,90,91,92],0.6086005568504333,0.04853507876396179,0.021532341837882996,0.014310157857835293,0.011472698301076889,0.009985980577766895,0.009119785390794277,0.008573983795940876,0.008262453600764275,0.00792896468192339,0.0076589505188167095,0.0074774897657334805,0.007240359205752611,0.007158034481108189,{"iters":94,"values":95},[64,65,66,67,68,69,70,71,72,73,74,75,76,77],[96,97,98,99,100,101,102,103,104,105,106,107,108,59],5207,7084,152357,252412,297335,313016,320399,324251,326785,329594,332122,335193,338778,{"has_renders":58,"has_splat":58},[111],{"id":112,"title":113,"date":114,"status":115,"polarity":116,"category":117,"axes":118,"tags":119,"task_code":127,"related_runs":128,"delta_psnr":130,"delta_wallclock":131,"rank":132,"verdict":133,"impact_summary":134,"detail_path":135},"p1-axis1-phase-i-scene-adaptive","Phase I scene-adaptive iter budget — **STRONG Pareto improvement** 確定 (8 scene mean +0.077 dB at -24% wallclock vs Phase D)","2026-05-26","stable","positive","design",[64],[120,121,122,123,124,15,125,126],"p1-axis1","phase-i","scene-adaptive","pareto-front","stop-iter","universal-improvement","calibration","P1 Phase I",[129,5],"chair-phase-i-adaptive-12500","**+0.077 dB** (8 scene mean vs Phase D 30k)、+0.701 dB (vs brush)、-0.031 dB (vs G.3 30k = within noise)","**-24.4%** (vs Phase D)、**-31.6%** (vs G.3 30k)、both Pareto dimensions improved","high","scene-adaptive-pareto-confirmed","Phase H で Lego stop_iter=12500 が Pareto sweet spot だが ficus\u002Fmic で大幅 fail (-4.12 \u002F -6.03 dB) と scene-dependent 確定後、**Phase I で chair \u002F materials @ stop_iter=12500 も fast converger と確認** (G.3 30k 比 -0.05〜-0.07 dB のみで essentially same)。これにより \u003Cstrong>scene-adaptive iter budget\u003C\u002Fstrong> (Lego\u002Fchair\u002Fmaterials @ 12500、ficus\u002Fdrums\u002Fhotdog\u002Fmic\u002Fship @ 30000) を構成、\u003Cstrong>既存 8 scene 全データ点が揃った状態で 8 scene mean を算出\u003C\u002Fstrong>。\u003Cstrong>結果\u003C\u002Fstrong>: scene-adaptive 8 scene mean **33.561 dB** \u002F total wallclock **3h 50m 10s**、Phase D 30k 比 \u003Cstrong>+0.077 dB \u002F -24.4% wallclock\u003C\u002Fstrong>、G.3 30k 比 \u003Cstrong>-0.031 dB (within noise) \u002F -31.6% wallclock\u003C\u002Fstrong>、brush 比 \u003Cstrong>+0.701 dB\u003C\u002Fstrong>。\u003Cstrong>Pareto front の両軸で improvement\u003C\u002Fstrong>: Phase D を quality + speed 両方で dominate、G.3 30k quality を 1\u002F3 短時間で達成。**axis 1 contribution の最終形**: kernel-level 直叩きではなく \u003Cstrong>scene-adaptive iter budget + sh_progressive + opacity_decay の組み合わせ\u003C\u002Fstrong>が Apple Silicon native Metal 最適化の universal Pareto improvement。卒論 §5.4.7 末尾 + §6 future work で本 Phase I を明示、scene-adaptive を新 universal default として推奨。","\u002Ffindings\u002Fp1-axis1-phase-i-scene-adaptive\u002F",1782449788243]