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DTSTAMP:20250522T212739Z
LOCATION:Bluebird Ballroom
DTSTART;TZID=America/Denver:20240728T180000
DTEND;TZID=America/Denver:20240728T204500
UID:siggraph_SIGGRAPH 2024_sess211_paperstog_101@linklings.com
SUMMARY:DMHomo: Learning Homography with Diffusion Models
DESCRIPTION:Haipeng Li (University of Electronic Science and Technology of
  China), Hai Jiang (Sichuan University), Ao Luo (Megvii Technology Limited
 ), Ping Tan (Hong Kong University of Science and Technology), Haoqiang Fan
  (Megvii Technology Limited), Bing Zeng and Shuaicheng Liu (University of 
 Electronic Science and Technology of China), and Haipeng Li\n\nDMHomo leve
 rages diffusion-models to generate a realistic dataset for homography lear
 ning. We train the generative model using pseudo labels. Additionally, we 
 introduce an iterative process that improves both the homography estimator
  and the diffusion models successively, producing a qualified dataset and 
 a state-of-the-art network.\n\nInterest Area: Arts & Design, Production & 
 Animation, Research & Education\n\nRecording: Livestreamed, Recorded\n\nRe
 gistration Category: Full Conference, Full Conference Supporter, Virtual A
 ccess, Experience, Exhibitor Full Conference, Exhibitor Experience, Sunday
 \n\n
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