10 accepted papers
Flicker artifacts, arising from unstable illumination and row-wise exposure inconsistencies, pose a significant challenge in short-exposure photography, severely degrading image quality. Unlike typical artifacts, e.g., noise and low-light, flicker is a structured degradation with specific spatial-te
Flicker artifacts in short-exposure images are caused by the interplay between the row-wise exposure mechanism of rolling shutter cameras and the temporal intensity variations of alternating current (AC)-powered lighting. These artifacts typically appear as uneven brightness distribution across the…
Transformer-based approaches have gained significant attention in image restoration, where the core component, i.e, Multi-Head Attention (MHA), plays a crucial role in capturing diverse features and recovering high-quality results. In MHA, heads perform attention calculation independently from unifo…
Lens flare occurs when shooting towards strong light sources, significantly degrading the visual quality of images. Due to the difficulty in capturing flare-corrupted and flare-free image pairs in the real world, existing datasets are typically synthesized in 2D by overlaying artificial flare templa…
Hand mesh reconstruction has attracted considerable attention in recent years with various approaches and techniques being proposed. Some of these methods incorporate complex components and designs which while effective may complicate the model and hinder efficiency. In this paper we decompose the m…
Transformer-based approaches have achieved promising performance in image restoration tasks given their ability to model long-range dependencies which is crucial for recovering clear images. Though diverse efficient attention mechanism designs have addressed the intensive computations associated wit…
"We interact with the world with our hands and see it through our own (egocentric) perspective. A holistic understanding of such interactions from egocentric views is important for tasks in robotics, AR/VR, action recognition and motion generation. Accurately reconstructing such interactions in is c…
"How to explore useful features from images as prompts to guide the deep image restoration models is an effective way to solve image restoration. In contrast to mining spatial relations within images as prompt, which leads to characteristics of different frequencies being neglected and further remai…
Recent studies have proven the strength of task-oriented point cloud sampling methods over traditional non-learned ones. However, previous task-oriented samplers are not adequate to extract local details and spatial patterns of point clouds, limiting the quality of synthesized points. In this paper,…
Fine-grained image classification is a challenging computer vision task where various species share similar visual appearances, resulting in misclassification if merely based on visual clues. Therefore, it is helpful to leverage additional information, e.g., the locations and dates for data shooting…