Search Results for author:
Found 11 papers, 7 papers with code
Sparse and Privacy-enhanced Representation for Human Pose Estimation
We propose a sparse and privacy-enhanced representation for Human Pose Estimation (HPE).
VMCML: Video and Music Matching via Cross-Modality Lifting
We propose a content-based system for matching video and background music.
MixFairFace: Towards Ultimate Fairness via MixFair Adapter in Face Recognition
In this paper, we propose MixFairFace framework to improve the fairness in face recognition models.
BiFuse++: Self-supervised and Efficient Bi-projection Fusion for 360 Depth Estimation
Thus, state-of-the-art frameworks for monocular 360 depth estimation such as bi-projection fusion in BiFuse are proposed.
Ranked #12 on
Depth Estimation
on Stanford2D3D Panoramic
LED2-Net: Monocular 360deg Layout Estimation via Differentiable Depth Rendering
Although significant progress has been made in room layout estimation, most methods aim to reduce the loss in the 2D pixel coordinate rather than exploiting the room structure in the 3D space.
LED2-Net: Monocular 360 Layout Estimation via Differentiable Depth Rendering
Although significant progress has been made in room layout estimation, most methods aim to reduce the loss in the 2D pixel coordinate rather than exploiting the room structure in the 3D space.
3D Room Layouts From A Single RGB Panorama
Depth Estimation
+2
BiFuse: Monocular 360 Depth Estimation via Bi-Projection Fusion
Depth estimation from a monocular 360 image is an emerging problem that gains popularity due to the availability of consumer-level 360 cameras and the complete surrounding sensing capability.
Ranked #15 on
Depth Estimation
on Stanford2D3D Panoramic
LayoutMP3D: Layout Annotation of Matterport3D
Inferring the information of 3D layout from a single equirectangular panorama is crucial for numerous applications of virtual reality or robotics (e. g., scene understanding and navigation).
Plug-and-Play: Improve Depth Estimation via Sparse Data Propagation
We propose a novel plug-and-play (PnP) module for improving depth prediction with taking arbitrary patterns of sparse depths as input.
DuLa-Net: A Dual-Projection Network for Estimating Room Layouts from a Single RGB Panorama
We present a deep learning framework, called DuLa-Net, to predict Manhattan-world 3D room layouts from a single RGB panorama.
Self-Supervised Learning of Depth and Camera Motion from 360° Videos
We propose a novel self-supervised learning approach for predicting the omnidirectional depth and camera motion from a 360{\deg} video.
