Search Results for author:
Found 9 papers, 5 papers with code
Self-Assessed Generation: Trustworthy Label Generation for Optical Flow and Stereo Matching in Real-world
A significant challenge facing current optical flow and stereo methods is the difficulty in generalizing them well to the real world.
Vision Transformer based Random Walk for Group Re-Identification
To this end, we propose a novel vision transformer based random walk framework for group re-ID.
ScaleFlow++: Robust and Accurate Estimation of 3D Motion from Video
Unlike previous methods, ScaleFlow++ integrates optical flow and MID estimation into a unified architecture, estimating optical flow and MID end-to-end based on feature matching.
Deep High-Resolution Representation Learning for Cross-Resolution Person Re-identification
Compared with the state-of-the-art methods, our proposed PS-HRNet improves 3. 4\%, 6. 2\%, 2. 5\%, 1. 1\% and 4. 2\% at Rank-1 on MLR-Market-1501, MLR-CUHK03, MLR-VIPeR, MLR-DukeMTMC-reID, and CAVIAR datasets, respectively.
TIPCB: A Simple but Effective Part-based Convolutional Baseline for Text-based Person Search
Text-based person search is a sub-task in the field of image retrieval, which aims to retrieve target person images according to a given textual description.
Ranked #13 on
Text based Person Retrieval
on CUHK-PEDES
Reference-Aided Part-Aligned Feature Disentangling for Video Person Re-Identification
Due to the inaccurate person detections and pose changes, pedestrian misalignment significantly increases the difficulty of feature extraction and matching.
Hybrid-Attention Guided Network with Multiple Resolution Features for Person Re-Identification
Finally, we reconstruct the feature extractor to ensure that our model can obtain more richer and robust features.
Cascade Convolutional Neural Network for Image Super-Resolution
With the development of the super-resolution convolutional neural network (SRCNN), deep learning technique has been widely applied in the field of image super-resolution.
Ranked #1 on
Image Super-Resolution
on BSD200 - 2x upscaling
An Efficient Algorithm for the Piecewise-Smooth Model with Approximately Explicit Solutions
This paper presents an efficient approach to image segmentation that approximates the piecewise-smooth (PS) functional in [12] with explicit solutions.
