Qualitative comparison figures are central evidence in computer vision papers, and vision-language models (VLMs) are increasingly used to judge them. Yet existing benchmarks score only scalar quality or overall preference, so a judge can be rewarded for picking the preferred image for the wrong visual reason. We introd...
Xuân Định Vũ, Duc-Hai Nguyen, M. Dao et al.· 0 citations
Image diffusion models have shown impressive image generation capabilities but are often hard to control, in contrast to classical computer graphics pipelines such as physically based rendering. However, we observe that there is a bridge between light transport phenomena and the distribution of latent space values prod...
V. Radovanović, Vishesh Gupta, Adrien Gruson et al.· 0 citations
This paper proposes a method to address gradient vanishing with a piecewise truncated gradient formulation that improves the optimization stability and robustness to initializations and introduces a novel dataset for benchmarking dynamic Gaussian Splatting using synthetic 3D scenes.
Théo Morales, Nhat-Quynh Le-Pham, Robin Atkins et al.· 0 citations
UniCaMo is presented, a unified framework that enables simultaneous control of object trajectories and camera viewpoints by directly constructing the input noise of the diffusion model and achieves state-of-the-art results in both video quality and motion controllability on standard controllable video generation benchm...
Long Vu, T. Ngô, Animesh Karnewar et al.· 0 citations
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