7 accepted papers
In this paper, we investigate the limitations of the Vector Quantized Latent Diffusion Model (VQ-LDM) in restoration tasks. We identify a performance gap between the Vector Quantization (VQ) and Diffusion Model components, manifested as a significant discrepancy between the reconstruction quality of
This paper investigates the reliable parking space search problem in structured environments, with the objective of minimizing the linear combination of mean and standard deviation (mean-std) parking space search time. While canonical parking space search algorithms usually target the minimal expect
This paper studies a risk-sensitive formulation of the multi-robot search problem, termed multi-robot mean-standard deviation search (MuRMSS), in which a team of robots cooperatively search for a moving target by minimizing a linear combination of the mean and standard deviation of search time. Howe
An effective pre-training framework with universal 3D representations is extremely desired in perceiving large-scale dynamic scenes. However establishing such an ideal framework that is both task-generic and label-efficient poses a challenge in unifying the representation of the same primitive acros…
In image editing, Denoising Diffusion Implicit Models (DDIM) inversion has become a widely adopted method and is extensively used in various image editing approaches. The core concept of DDIM inversion stems from the deterministic sampling technique of DDIM, which allows the DDIM process to be viewe…
Multi-frame human pose estimation has long been a compelling and fundamental problem in computer vision. This task is challenging due to fast motion and pose occlusion that frequently occur in videos. State-of-the-art methods strive to incorporate additional visual evidences from neighboring frames…
Multi-frame human pose estimation in complicated situations is challenging. Although state-of-the-art human joints detectors have demonstrated remarkable results for static images, their performances come short when we apply these models to video sequences. Prevalent shortcomings include the failure…