20 citations · 28 across the 8 of their papers we have counts for
9 papers · 1 filter
ActiveRMAP: Radiance Field for Active Mapping And Planning
Huangying Zhan, Jiyang Zheng, Yi Xu +2
A high-quality 3D reconstruction of a scene from a collection of 2D images can be achieved through offline/online mapping methods. In this paper, we explore active mapping from the…
CLIP-FLow: Contrastive Learning by semi-supervised Iterative Pseudo labeling for Optical Flow Estimation
Zhiqi Zhang, Nitin Bansal, Changjiang Cai +4
Synthetic datasets are often used to pretrain end-to-end optical flow networks, due to the lack of a large amount of labeled, real-scene data. But major drops in accuracy occur whe…
FisheyeDistill: Self-Supervised Monocular Depth Estimation with Ordinal Distillation for Fisheye Cameras
Qingan Yan, Pan Ji, Nitin Bansal +3
In this paper, we deal with the problem of monocular depth estimation for fisheye cameras in a self-supervised manner. A known issue of self-supervised depth estimation is that it…
GeoRefine: Self-Supervised Online Depth Refinement for Accurate Dense Mapping
Pan Ji, Qingan Yan, Yuxin Ma +1
We present a robust and accurate depth refinement system, named GeoRefine, for geometrically-consistent dense mapping from monocular sequences. GeoRefine consists of three modules:…
Deformable VisTR: Spatio temporal deformable attention for video instance segmentation
Sudhir Yarram, Jialian Wu, Pan Ji +2
Video instance segmentation (VIS) task requires classifying, segmenting, and tracking object instances over all frames in a video clip. Recently, VisTR has been proposed as end-to-…
Object Detection in the Context of Mobile Augmented Reality
Xiang Li, Yuan Tian, Fuyao Zhang +2
In the past few years, numerous Deep Neural Network (DNN) models and frameworks have been developed to tackle the problem of real-time object detection from RGB images. Ordinary ob…