Generative adversarial networks (GANs) have been extensively studied in the past few
years. Arguably their most significant impact has been in the area of computer vision where …

As a common image editing operation, image composition aims to combine the foreground
from one image and another background image, resulting in a composite image. However …

Object compositing based on 2D images is a challenging problem since it typically involves
multiple processing stages such as color harmonization, geometry correction and shadow …

We present the first systematic study on concealed object detection (COD), which aims to
identify objects that are visually embedded in their background. The high intrinsic similarities …

Interactive segmentation allows users to extract target masks by making positive/negative
clicks. Although explored by many previous works, there is still a gap between academic …

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 …

Existing semantic segmentation works have been mainly focused on designing effective
decoders; however, the computational load introduced by the overall structure has long …

We present a systematic study on a new task called dichotomous image segmentation (DIS),
which aims to segment highly accurate objects from natural images. To this end, we …

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 present an end-to-end deep learning architecture for depth map inference from multi-
view images. In the network, we first extract deep visual image features, and then build the …