research
∙
09/21/2023
MoDA: Leveraging Motion Priors from Videos for Advancing Unsupervised Domain Adaptation in Semantic Segmentation
Unsupervised domain adaptation (UDA) is an effective approach to handle ...
share
research
∙
07/19/2022
ML-BPM: Multi-teacher Learning with Bidirectional Photometric Mixing for Open Compound Domain Adaptation in Semantic Segmentation
Open compound domain adaptation (OCDA) considers the target domain as th...
research
∙
10/13/2021
Attentive and Contrastive Learning for Joint Depth and Motion Field Estimation
Estimating the motion of the camera together with the 3D structure of th...
research
∙
08/12/2021
Correlate-and-Excite: Real-Time Stereo Matching via Guided Cost Volume Excitation
Volumetric deep learning approach towards stereo matching aggregates a c...
research
∙
03/01/2021
Unsupervised Depth and Ego-motion Estimation for Monocular Thermal Video using Multi-spectral Consistency Loss
Most of the deep-learning based depth and ego-motion networks have been ...
research
∙
02/04/2021
Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency
We present an end-to-end joint training framework that explicitly models...
research
∙
10/23/2020
ResNet or DenseNet? Introducing Dense Shortcuts to ResNet
ResNet or DenseNet? Nowadays, most deep learning based approaches are im...
research
∙
04/16/2020
Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision
Convolutional neural network-based approaches have achieved remarkable p...
research
∙
12/19/2019
Instance-wise Depth and Motion Learning from Monocular Videos
We present an end-to-end joint training framework that explicitly models...
research
∙
09/16/2019
Learning Residual Flow as Dynamic Motion from Stereo Videos
We present a method for decomposing the 3D scene flow observed from a mo...
research
∙
09/16/2019
Visuomotor Understanding for Representation Learning of Driving Scenes
Dashboard cameras capture a tremendous amount of driving scene video eac...
research
∙
04/17/2019
Variational Prototyping-Encoder: One-Shot Learning with Prototypical Images
In daily life, graphic symbols, such as traffic signs and brand logos, a...
research
∙
12/05/2017
Co-domain Embedding using Deep Quadruplet Networks for Unseen Traffic Sign Recognition
Recent advances in visual recognition show overarching success by virtue...
research
∙
10/17/2017