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DTSTAMP:20260417T190158Z
LOCATION:West Building\, Rooms 118-120
DTSTART;TZID=America/Los_Angeles:20250813T104500
DTEND;TZID=America/Los_Angeles:20250813T105500
UID:siggraph_SIGGRAPH 2025_sess152_papers_331@linklings.com
SUMMARY:Be Decisive: Noise-Induced Layouts for Multi-Subject Generation
DESCRIPTION:Omer Dahary (Tel Aviv University, Snap Research); Yehonathan C
 ohen (Tel Aviv University); Or Patashnik (Tel Aviv University, Snap Resear
 ch); Kfir Aberman (Snap Research); and Daniel Cohen-Or (Tel Aviv Universit
 y, Snap Research)\n\nText-to-image diffusion models struggle with multi-su
 bject generation due to subject leakage. Prior methods impose external lay
 outs that conflict with the model’s prior, harming alignment and natural c
 omposition. We introduce a method that leverages the layout encoded in the
  initial noise, promoting alignment and natural compositions while preserv
 ing the model’s diversity.\n\nInterest Area: Research & Education\n\nRecor
 ding: Livestreamed, Not Livestreamed, Recorded, Not Recorded\n\nRegistrati
 on Category: Full Conference, Virtual Access, Wednesday\n\nSession Chair: 
 Or Patashnik (Tel Aviv University, Snap Research)\n\n
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