11 accepted papers
Brain visual decoding aims to recognize and reconstruct perceptual visual content from brain activity, providing a promising potential for the development of brain-computer interfaces and brain-inspired intelligence. However, this task faces a fundamental challenge of information asymmetry: while na
As a fundamental visual task, optical flow estimation has widespread applications in computer vision. However, it faces significant challenges under adverse lighting conditions, where low texture and noise make accurate optical flow estimation particularly difficult.In this paper, we propose an opti…
Targeting the notorious cumulative drift errors in NeRF SLAM, we propose a Semantic-guided Loop Closure using Shared Latent Code, dubbed SLC<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{2}$</tex-math></inline-f
Visual place recognition (VPR) is essential to many autonomous systems. Existing VPR methods demonstrate attractive performance at the cost of limited generalizability. When deployed in unseen environments, these methods exhibit significant performance drops. Targeting this issue, we present VIPeR,
We present AEGIS-Net, a novel indoor place recognition model that takes in RGB point clouds and generates global place descriptors by aggregating lower-level color, geometry features and higher-level implicit semantic features. However, rather than simple feature concatenation, self-attention module…
Neural Radiance Fields have shown great potential to synthesize novel views with only a few discrete image observations of the world. However, the requirement of accurate camera parameters to learn scene representations limits its further application. In this paper, we present adaptive positional en…
In this paper, we propose a continuous-time-based LiDAR-inertial-vehicle odometry method, which can tightly fuse the data from Light Detection And Ranging (LiDAR), inertial measurement units (IMU), and vehicle measurements. The lateral acceleration constraint is further added to trajectory estimatio…
Traditional Visual Odometry (VO) methods that utilize visible cameras frequently degrade in challenging illumination environments. Alternative vision sensors such as thermal cameras are promising for all-day navigation since the delivered thermal images are invariant to ambient illumination. However
In recent years, longwave infrared (LWIR) cameras have become potential in visual simultaneous localization and mapping (SLAM) research since the delivered thermal images can provide information beyond the visible spectrum and are robust to environment illumination. However, due to modality differen
Visible images have been widely used for motion estimation. Thermal images, in contrast, are more challenging to be used in motion estimation since they typically have lower resolution, less texture, and more noise. In this paper, a novel dataset for evaluating the performance of multi-spectral moti…
Since visible cameras rely on ideal illumination to provide adequate environment information, visual simultaneous localization and mapping (SLAM) under extreme illumination remains a challenge. Therefore, we propose a direct near-infrared-depth visual SLAM method with an active near-infrared (NIR) l