6 papers
SounDiT: Geo-Contextual Soundscape-to-Landscape Generation
Junbo Wang, Haofeng Tan, Bowen Liao +7
Recent audio-to-image models have shown impressive performance in generating images of specific objects conditioned on their corresponding sounds. However, these models fail to rec…
Positional Encoding Field
Yunpeng Bai, Haoxiang Li, Qixing Huang
Diffusion Transformers (DiTs) have emerged as the dominant architecture for visual generation, powering state-of-the-art image and video models. By representing images as patch tok…
Escaping Plato's Cave: Towards the Alignment of 3D and Text Latent Spaces
Souhail Hadgi, Luca Moschella, Andrea Santilli +5
Recent works have shown that, when trained at scale, uni-modal 2D vision and text encoders converge to learned features that share remarkable structural properties, despite arising…
P3P: Pseudo-3D Pre-training for Scaling 3D Voxel-based Masked Autoencoders
Xuechao Chen, Ying Chen, Jialin Li +5
3D pre-training is crucial to 3D perception tasks. Nevertheless, limited by the difficulties in collecting clean and complete 3D data, 3D pre-training has persistently faced data s…
PASTA: Part-Aware Sketch-to-3D Shape Generation with Text-Aligned Prior
Seunggwan Lee, Hwanhee Jung, Byoungsoo Koh +3
A fundamental challenge in conditional 3D shape generation is to minimize the information loss and maximize the intention of user input. Existing approaches have predominantly focu…
FiffDepth: Feed-forward Transformation of Diffusion-Based Generators for Detailed Depth Estimation
Yunpeng Bai, Qixing Huang
Monocular Depth Estimation (MDE) is a fundamental 3D vision problem with numerous applications such as 3D scene reconstruction, autonomous navigation, and AI content creation. Howe…