6 citations · 6 across the 3 of their papers we have counts for
Showing cs.CVShow all
3 papers · 1 filter
cs.CV2026
PixelDiT2: Representation-Grounded Pixel Diffusion Transformers
Yongsheng Yu, Wei Xiong, Yichen Sheng +2
Recent advances in pixel-space diffusion models have narrowed the image quality gap with latent-space diffusion, but still converge more slowly and lag behind in final image qualit…
cs.CV2026
RGBX-Next: Towards Realistic Generative Rendering from G-Buffers
Zheng Zeng, Marco Salvi, Lifan Wu +9
Diffusion models have achieved impressive results in image, video, and streaming generation. However, compared to traditional 3D rendering, they still lack precise control over the…
cs.CV2020★ 6 cited
Transposer: Universal Texture Synthesis Using Feature Maps as Transposed Convolution Filter
Guilin Liu, Rohan Taori, Ting-Chun Wang +6
Conventional CNNs for texture synthesis consist of a sequence of (de)-convolution and up/down-sampling layers, where each layer operates locally and lacks the ability to capture th…