85 citations · 114 across the 8 of their papers we have counts for
8 papers · 1 filter
MonoNeRD: NeRF-like Representations for Monocular 3D Object Detection
Junkai Xu, Liang Peng, Haoran Cheng +5
In the field of monocular 3D detection, it is common practice to utilize scene geometric clues to enhance the detector's performance. However, many existing works adopt these clues…
BNV-Fusion: Dense 3D Reconstruction using Bi-level Neural Volume Fusion
Kejie Li, Yansong Tang, Victor Adrian Prisacariu +1
Dense 3D reconstruction from a stream of depth images is the key to many mixed reality and robotic applications. Although methods based on Truncated Signed Distance Function (TSDF)…
ODAM: Object Detection, Association, and Mapping using Posed RGB Video
Kejie Li, Daniel DeTone, Steven Chen +6
Localizing objects and estimating their extent in 3D is an important step towards high-level 3D scene understanding, which has many applications in Augmented Reality and Robotics.…
Ray-ONet: Efficient 3D Reconstruction From A Single RGB Image
Wenjing Bian, Zirui Wang, Kejie Li +1
We propose Ray-ONet to reconstruct detailed 3D models from monocular images efficiently. By predicting a series of occupancy probabilities along a ray that is back-projected from a…
MOLTR: Multiple Object Localisation, Tracking, and Reconstruction from Monocular RGB Videos
Kejie Li, Hamid Rezatofighi, Ian Reid
Semantic aware reconstruction is more advantageous than geometric-only reconstruction for future robotic and AR/VR applications because it represents not only where things are, but…
FroDO: From Detections to 3D Objects
Kejie Li, Martin Rünz, Meng Tang +8
Object-oriented maps are important for scene understanding since they jointly capture geometry and semantics, allow individual instantiation and meaningful reasoning about objects.…
Single-view Object Shape Reconstruction Using Deep Shape Prior and Silhouette
Kejie Li, Ravi Garg, Ming Cai +1
3D shape reconstruction from a single image is a highly ill-posed problem. Modern deep learning based systems try to solve this problem by learning an end-to-end mapping from image…
Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction
Huangying Zhan, Ravi Garg, Chamara Saroj Weerasekera +3
Despite learning based methods showing promising results in single view depth estimation and visual odometry, most existing approaches treat the tasks in a supervised manner. Recen…