11 citations · 13 across the 11 of their papers we have counts for
12 papers · 1 filter
On Aligning Hierarchical Standardized Embedding for Audio-visual Generalized Zero-shot Learning
Zihan Zhang, Jie Hong, Siyuan Fan +2
Audio-visual Generalized Zero-shot Learning (AV-GZSL) is a challenging task that aims to classify both seen and unseen objects or scenes by integrating data from audio and visual m…
Backpropagation-free Network for 3D Test-time Adaptation
Yanshuo Wang, Ali Cheraghian, Zeeshan Hayder +7
Real-world systems often encounter new data over time, which leads to experiencing target domain shifts. Existing Test-Time Adaptation (TTA) methods tend to apply computationally h…
Continual Test-time Domain Adaptation via Dynamic Sample Selection
Yanshuo Wang, Jie Hong, Ali Cheraghian +4
The objective of Continual Test-time Domain Adaptation (CTDA) is to gradually adapt a pre-trained model to a sequence of target domains without accessing the source data. This pape…
Hyperbolic Audio-visual Zero-shot Learning
Jie Hong, Zeeshan Hayder, Junlin Han +3
Audio-visual zero-shot learning aims to classify samples consisting of a pair of corresponding audio and video sequences from classes that are not present during training. An analy…
PointCaM: Cut-and-Mix for Open-Set Point Cloud Learning
Jie Hong, Shi Qiu, Weihao Li +4
Point cloud learning is receiving increasing attention. However, most existing point cloud models lack the practical ability to deal with the unavoidable presence of unknown object…
What Images are More Memorable to Machines?
Junlin Han, Huangying Zhan, Jie Hong +4
This paper studies the problem of measuring and predicting how memorable an image is to pattern recognition machines, as a path to explore machine intelligence. Firstly, we propose…
Curved Geometric Networks for Visual Anomaly Recognition
Jie Hong, Pengfei Fang, Weihao Li +3
Learning a latent embedding to understand the underlying nature of data distribution is often formulated in Euclidean spaces with zero curvature. However, the success of the geomet…
Towards Open-Set Object Detection and Discovery
Jiyang Zheng, Weihao Li, Jie Hong +2
With the human pursuit of knowledge, open-set object detection (OSOD) has been designed to identify unknown objects in a dynamic world. However, an issue with the current setting i…
GOSS: Towards Generalized Open-set Semantic Segmentation
Jie Hong, Weihao Li, Junlin Han +4
In this paper, we present and study a new image segmentation task, called Generalized Open-set Semantic Segmentation (GOSS). Previously, with the well-known open-set semantic segme…
You Only Cut Once: Boosting Data Augmentation with a Single Cut
Junlin Han, Pengfei Fang, Weihao Li +5
We present You Only Cut Once (YOCO) for performing data augmentations. YOCO cuts one image into two pieces and performs data augmentations individually within each piece. Applying…
Blind Image Decomposition
Junlin Han, Weihao Li, Pengfei Fang +5
We propose and study a novel task named Blind Image Decomposition (BID), which requires separating a superimposed image into constituent underlying images in a blind setting, that…
Reinforced Attention for Few-Shot Learning and Beyond
Jie Hong, Pengfei Fang, Weihao Li +4
Few-shot learning aims to correctly recognize query samples from unseen classes given a limited number of support samples, often by relying on global embeddings of images. In this…