research
∙
03/26/2023
POAR: Towards Open-World Pedestrian Attribute Recognition
Pedestrian attribute recognition (PAR) aims to predict the attributes of...
share
research
∙
02/28/2023
Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger
Recent deep-learning-based compression methods have achieved superior pe...
research
∙
02/28/2023
Temporal Coherent Test-Time Optimization for Robust Video Classification
Deep neural networks are likely to fail when the test data is corrupted ...
research
∙
03/31/2022
Towards Robust Rain Removal Against Adversarial Attacks: A Comprehensive Benchmark Analysis and Beyond
Rain removal aims to remove rain streaks from images/videos and reduce t...
research
∙
10/13/2021
Benchmarking the Robustness of Spatial-Temporal Models Against Corruptions
The state-of-the-art deep neural networks are vulnerable to common corru...
research
∙
09/30/2020
Attention-Aware Noisy Label Learning for Image Classification
Deep convolutional neural networks (CNNs) learned on large-scale labeled...
research
∙
09/15/2019
Scaling Object Detection by Transferring Classification Weights
Large scale object detection datasets are constantly increasing their si...
research
∙
01/29/2018
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
It is desirable to train convolutional networks (CNNs) to run more effic...
research
∙
11/17/2016