7 accepted papers
Tracking any point (TAP) is a fundamental yet challenging task in computer vision, requiring high precision and long-term motion reasoning. Recent attempts to combine RGB frames and event streams have shown promise, yet they typically rely on synchronous or non-adaptive fusion, leading to temporal m
Existing image reflection removal methods struggle to handle complex reflections. Accurate language descriptions can help the model understand the image content to remove complex reflections. However, due to blurred and distorted interferences in reflected images, machine-generated language descript
The integration of image and event streams offers a promising approach for achieving robust visual object tracking in complex environments. However, current fusion methods achieve high performance at the cost of significant computational overhead and struggle to efficiently extract the sparse, async…
Visual localization refers to the process of determining camera poses and orientation within a known scene representation. This task is often complicated by factors such as changes in illumination and variations in viewing angles. In this paper, we propose HGSLoc, a novel lightweight plug-and-play p
The conditional diffusion models have made significant progress in image synthesis, leveraging human annotations such as class labels or text descriptions to guide the generative process. However, different from image synthesis, low-light image enhancement(LLIE) lacks strictly calibrated conditional…
Tracking any point based on image frames is constrained by frame rates, leading to instability in high-speed scenarios and limited generalization in real-world applications. To overcome these limitations, we propose an image-event fusion point tracker, FE-TAP, which combines the contextual informati
Most of the previous exposure correction methods learn dense pixel-wise transformations to achieve promising results but consume huge computational resources. Recently Learnable 3D lookup tables (3D LUTs) have demonstrated impressive performance and efficiency for image enhancement. However these me…