Balance-Aware Grid Collage for Small Image Collections

Yu Song, Fan Tang, Weiming Dong, Feiyue Huang, Tong Yee Lee, Changsheng Xu

研究成果: Article同行評審


Grid collages (GClg) of small image collections are popular and useful in many applications, such as personal album management, online photo posting, and graphic design. In this study, we focus on how visual effects influence individual preferences through various arrangements of multiple images under such scenarios. A novel balance-aware metric is proposed to bridge the gap between multi-image joint presentation and visual pleasure. The metric merges psychological achievements into the field of grid collage. To capture user preference, a bonus mechanism related to a user-specified special location in the grid and uniqueness values of the subimages is integrated into the metric. An end-to-end reinforcement learning mechanism empowers the model without tedious manual annotations. Experiments demonstrate that our metric can evaluate the GClg visual balance in line with human subjective perception, and the model can generate visually pleasant GClg results, which is comparable to manual designs.

All Science Journal Classification (ASJC) codes

  • 軟體
  • 訊號處理
  • 電腦視覺和模式識別
  • 電腦繪圖與電腦輔助設計


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