Search Results for author:
Found 9 papers, 5 papers with code
Behind the Veil: Enhanced Indoor 3D Scene Reconstruction with Occluded Surfaces Completion
The 3D Inpainter with abstract representation at coarse levels is trained offline using various scenes to complete occluded surfaces.
TCLC-GS: Tightly Coupled LiDAR-Camera Gaussian Splatting for Surrounding Autonomous Driving Scenes
Most 3D Gaussian Splatting (3D-GS) based methods for urban scenes initialize 3D Gaussians directly with 3D LiDAR points, which not only underutilizes LiDAR data capabilities but also overlooks the potential advantages of fusing LiDAR with camera data.
SeaBird: Segmentation in Bird's View with Dice Loss Improves Monocular 3D Detection of Large Objects
We argue that the cause of failure is the sensitivity of depth regression losses to noise of larger objects.
3D Object Detection
3D Object Detection From Monocular Images
+3
UPNeRF: A Unified Framework for Monocular 3D Object Reconstruction and Pose Estimation
Monocular 3D reconstruction for categorical objects heavily relies on accurately perceiving each object's pose.
3D Copy-Paste: Physically Plausible Object Insertion for Monocular 3D Detection
A major challenge in monocular 3D object detection is the limited diversity and quantity of objects in real datasets.
OmniFusion: 360 Monocular Depth Estimation via Geometry-Aware Fusion
In this paper, we propose a 360 monocular depth estimation pipeline, OmniFusion, to tackle the spherical distortion issue.
Ranked #6 on
Depth Estimation
on Stanford2D3D Panoramic
PoP-Net: Pose over Parts Network for Multi-Person 3D Pose Estimation from a Depth Image
In this paper, a real-time method called PoP-Net is proposed to predict multi-person 3D poses from a depth image.
Gen-LaneNet: A Generalized and Scalable Approach for 3D Lane Detection
The method, inspired by the latest state-of-the-art 3D-LaneNet, is a unified framework solving image encoding, spatial transform of features and 3D lane prediction in a single network.
Ranked #8 on
3D Lane Detection
on Apollo Synthetic 3D Lane
Robust pose tracking with a joint model of appearance and shape
We present a novel approach for estimating the 2D pose of an articulated object with an application to automated video analysis of small laboratory animals.
