5 accepted papers
Utilizing deep learning techniques for spacecraft pose estimation enables using low-cost sensors like monocular cameras. However, the existing methods have drawbacks, such as complex models or low estimation accuracy. Therefore, this letter proposes the Spacecraft Discrete Pose Estimation Network (S
Reliable pose estimation of non-cooperative spacecraft is a key technology for on-orbit servicing and active space debris removal missions. Currently, deep learning has become the mainstream method for spacecraft pose estimation. However, existing methods suffer from problems such as excessive param
Transformers have made great progress in dealing with computer vision tasks. However, existing vision transformers have not yet possessed the ability of building the interactions among features of different scales, which is perceptually important to visual inputs. The reasons are two-fold: (1) Input…
We present a transformer-based network, Human Mesh Deformer (HMD-former), to tackle the problem of 3D human mesh reconstruction from a single RGB image. HMD-former applies a pre-trained CNN to extract image grid features and a transformer decoder to gradually warp the template 3D mesh to the deforme…
Due to overly relying on appearance information or adopting direct static feature fusion, most of the existing action recognition methods based on multi-modality have poor robustness and insufficient consideration of modality differences. To address these problems, we propose a two-stream adaptive w…