Search Results for author:
Found 7 papers, 1 papers with code
Deep Progressive Feature Aggregation Network for High Dynamic Range Imaging
The primary challenges are ghosting artifacts caused by object motion between low dynamic range images and distorted content in under and overexposed regions.
Consistency of Implicit and Explicit Features Matters for Monocular 3D Object Detection
This paper studies 3D intermediate representation methods which generate intermediate 3D features for subsequent tasks.
Ranked #1 on
Monocular 3D Object Detection
on KITTI Cars Moderate
(using extra training data)
Single-image Defocus Deblurring by Integration of Defocus Map Prediction Tracing the Inverse Problem Computation
Considering the spatial variant property of the defocus blur and the blur level indicated in the defocus map, we employ the defocus map as conditional guidance to adjust the features from the input blurring images instead of simple concatenation.
Learning Regularized Multi-Scale Feature Flow for High Dynamic Range Imaging
Reconstructing ghosting-free high dynamic range (HDR) images of dynamic scenes from a set of multi-exposure images is a challenging task, especially with large object motion and occlusions, leading to visible artifacts using existing methods.
Qtrade AI at SemEval-2022 Task 11: An Unified Framework for Multilingual NER Task
This paper describes our system, which placed third in the Multilingual Track (subtask 11), fourth in the Code-Mixed Track (subtask 12), and seventh in the Chinese Track (subtask 9) in the SemEval 2022 Task 11: MultiCoNER Multilingual Complex Named Entity Recognition.
Progressive and Selective Fusion Network for High Dynamic Range Imaging
We propose a novel method that can better fuse the features based on two ideas.
Using LDA and LSTM Models to Study Public Opinions and Critical Groups Towards Congestion Pricing in New York City through 2007 to 2019
This study explores how people view and respond to the proposals of NYC congestion pricing evolve in time.
