3 papers
cs.CV2026
WAVE: Wavelet-Controlled Coarse-to-Fine Guidance for Depth Super-Resolution
Tayyab Nasir, Daochang Liu, Ajmal Mian
Guided depth super-resolution (GDSR) typically extracts RGB guidance features through convolutional hierarchies, inheriting their fine-to-coarse bias. Thus, low-level spatial cues…
eess.IV2026
NAIMA: Semantics Aware RGB Guided Depth Super-Resolution
Tayyab Nasir, Daochang Liu, Ajmal Mian
Guided depth super-resolution (GDSR) is a multi-modal approach for depth map super-resolution that relies on a low-resolution depth map and a high-resolution RGB image to restore f…
cs.CV2024
Learning Coherent Matrixized Representation in Latent Space for Volumetric 4D Generation
Qitong Yang, Mingtao Feng, Zijie Wu +4
Directly learning to model 4D content, including shape, color, and motion, is challenging. Existing methods rely on pose priors for motion control, resulting in limited motion dive…