Images captured in hazy or foggy weather conditions can be seriously degraded by
scattering of atmospheric particles, which reduces the contrast, changes the color, and …

Matting refers to the problem of accurate foreground estimation in images and video. It is
one of the key techniques in many image editing and film production applications, thus has …

Image matting is an inverse fusion process that separates the foreground and background
information by predicting alpha matte for each pixel. Recently, plain vision Transformers …

We introduce a robust, real-time, high-resolution human video matting method that achieves
new state-of-the-art performance. Our method is much lighter than previous approaches and …

We introduce a real-time, high-resolution background replacement technique which
operates at 30fps in 4K resolution, and 60fps for HD on a modern GPU. Our technique is …

Image matting is a fundamental computer vision problem and has many applications.
Previous algorithms have poor performance when an image has similar foreground and …

We propose a method for creating a matte-the per-pixel foreground color and alpha-of a
person by taking photos or videos in an everyday setting with a handheld camera. Most …

In this paper, we propose a transformer-based image matting model called MatteFormer,
which takes full advantage of trimap information in the transformer block. Our method first …

Existing deep learning based matting algorithms primarily resort to high-level semantic
features to improve the overall structure of alpha mattes. However, we argue that advanced …

We show that existing upsampling operators can be unified using the notion of the index
function. This notion is inspired by an observation in the decoding process of deep image …