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Unsupervised Structural Scene Decomposition via Foreground-Aware Slot Attention with Pseudo-Mask Guidance
Huankun Sheng, Ming Li, Yixiang Wei +4
Recent advances in object-centric representation learning have shown that slot attention-based methods can effectively decompose visual scenes into object slot representations with…
InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective
Yuanhong Zhang, Muyao Yuan, Weizhan Zhang +4
The Segment Anything Model (SAM), a vision foundation model, exhibits impressive zero-shot capabilities in general tasks but struggles in specialized domains. Parameter-efficient f…
Rectified Diffusion Guidance for Conditional Generation
Mengfei Xia, Nan Xue, Yujun Shen +3
Classifier-Free Guidance (CFG), which combines the conditional and unconditional score functions with two coefficients summing to one, serves as a practical technique for diffusion…
SpotActor: Training-Free Layout-Controlled Consistent Image Generation
Jiahao Wang, Caixia Yan, Weizhan Zhang +6
Text-to-image diffusion models significantly enhance the efficiency of artistic creation with high-fidelity image generation. However, in typical application scenarios like comic b…
Accelerating Non-Maximum Suppression: A Graph Theory Perspective
King-Siong Si, Lu Sun, Weizhan Zhang +4
Non-maximum suppression (NMS) is an indispensable post-processing step in object detection. With the continuous optimization of network models, NMS has become the ``last mile'' to…
OneActor: Consistent Character Generation via Cluster-Conditioned Guidance
Jiahao Wang, Caixia Yan, Haonan Lin +5
Text-to-image diffusion models benefit artists with high-quality image generation. Yet their stochastic nature hinders artists from creating consistent images of the same subject.…