Search Results for author:
Found 13 papers, 4 papers with code
Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition
Benchmarking our model on one of the most popular unconstrained face recognition datasets IJB-C additionally verifies the promising generalizability of AIM in recognizing faces in the wild.
Ranked #1 on
Age-Invariant Face Recognition
on MORPH Album2
Intention-Net: Integrating Planning and Deep Learning for Goal-Directed Autonomous Navigation
How can a delivery robot navigate reliably to a destination in a new office building, with minimal prior information?
A Good Practice Towards Top Performance of Face Recognition: Transferred Deep Feature Fusion
In this paper, we propose a unified learning framework named Transferred Deep Feature Fusion (TDFF) targeting at the new IARPA Janus Benchmark A (IJB-A) face recognition dataset released by NIST face challenge.
DAMSL: Domain Agnostic Meta Score-based Learning
In this paper, we propose Domain Agnostic Meta Score-based Learning (DAMSL), a novel, versatile and highly effective solution that delivers significant out-performance over state-of-the-art methods for cross-domain few-shot learning.
Ranked #1 on
Cross-Domain Few-Shot
on miniImagenet
Person re-identification with fusion of hand-crafted and deep pose-based body region features
Person re-identification (re-ID) aims to accurately re- trieve a person from a large-scale database of images cap- tured across multiple cameras.
Scale-aware Fast R-CNN for Pedestrian Detection
Taking pedestrian detection as an example, we illustrate how we can leverage this philosophy to develop a Scale-Aware Fast R-CNN (SAF R-CNN) framework.
Ranked #23 on
Pedestrian Detection
on Caltech
Detecting The Objects on The Road Using Modular Lightweight Network
In order to solve this problem, majority of existing methods utilize complicated network or bigger image size, which generally leads to higher computation cost.
Towards Pose Invariant Face Recognition in the Wild
To this end, we propose a Pose Invariant Model (PIM) for face recognition in the wild, with three distinct novelties.
Cross-Resolution Face Recognition via Prior-Aided Face Hallucination and Residual Knowledge Distillation
Recent deep learning based face recognition methods have achieved great performance, but it still remains challenging to recognize very low-resolution query face like 28x28 pixels when CCTV camera is far from the captured subject.
Data Augmentation Imbalance For Imbalanced Attribute Classification
Pedestrian attribute recognition is an important multi-label classification problem.
Speaker-Utterance Dual Attention for Speaker and Utterance Verification
The proposed SUDA features an attention mask mechanism to learn the interaction between the speaker and utterance information streams.
Efficient High-Dimensional Data Representation Learning via Semi-Stochastic Block Coordinate Descent Methods
To address this issue, we propose a novel hard thresholding algorithm, called Semi-stochastic Block Coordinate Descent Hard Thresholding Pursuit (SBCD-HTP).
Exploring Invariant Representation for Visible-Infrared Person Re-Identification
Cross-spectral person re-identification, which aims to associate identities to pedestrians across different spectra, faces a main challenge of the modality discrepancy.
