20 citations · 39 across the 14 of their papers we have counts for
14 papers
ICAR: Image-based Complementary Auto Reasoning
Xijun Wang, Anqi Liang, Junbang Liang +3
Scene-aware Complementary Item Retrieval (CIR) is a challenging task which requires to generate a set of compatible items across domains. Due to the subjectivity, it is difficult t…
SCSC: Spatial Cross-scale Convolution Module to Strengthen both CNNs and Transformers
Xijun Wang, Xiaojie Chu, Chunrui Han +1
This paper presents a module, Spatial Cross-scale Convolution (SCSC), which is verified to be effective in improving both CNNs and Transformers. Nowadays, CNNs and Transformers hav…
Triplet Knowledge Distillation
Xijun Wang, Dongyang Liu, Meina Kan +3
In Knowledge Distillation, the teacher is generally much larger than the student, making the solution of the teacher likely to be difficult for the student to learn. To ease the mi…
SCP: Soft Conditional Prompt Learning for Aerial Video Action Recognition
Xijun Wang, Ruiqi Xian, Tianrui Guan +2
We present a new learning approach, Soft Conditional Prompt Learning (SCP), which leverages the strengths of prompt learning for aerial video action recognition. Our approach is de…
Atmospheric Turbulence Correction via Variational Deep Diffusion
Xijun Wang, Santiago López-Tapia, Aggelos K. Katsaggelos
Atmospheric Turbulence (AT) correction is a challenging restoration task as it consists of two distortions: geometric distortion and spatially variant blur. Diffusion models have s…
Video-Specific Query-Key Attention Modeling for Weakly-Supervised Temporal Action Localization
Xijun Wang, Aggelos K. Katsaggelos
Weakly-supervised temporal action localization aims to identify and localize the action instances in the untrimmed videos with only video-level action labels. When humans watch vid…
PMI Sampler: Patch Similarity Guided Frame Selection for Aerial Action Recognition
Ruiqi Xian, Xijun Wang, Divya Kothandaraman +1
We present a new algorithm for selection of informative frames in video action recognition. Our approach is designed for aerial videos captured using a moving camera where human ac…
AZTR: Aerial Video Action Recognition with Auto Zoom and Temporal Reasoning
Xijun Wang, Ruiqi Xian, Tianrui Guan +4
We propose a novel approach for aerial video action recognition. Our method is designed for videos captured using UAVs and can run on edge or mobile devices. We present a learning-…
CrossLoc3D: Aerial-Ground Cross-Source 3D Place Recognition
Tianrui Guan, Aswath Muthuselvam, Montana Hoover +5
We present CrossLoc3D, a novel 3D place recognition method that solves a large-scale point matching problem in a cross-source setting. Cross-source point cloud data corresponds to…
MITFAS: Mutual Information based Temporal Feature Alignment and Sampling for Aerial Video Action Recognition
Ruiqi Xian, Xijun Wang, Dinesh Manocha
We present a novel approach for action recognition in UAV videos. Our formulation is designed to handle occlusion and viewpoint changes caused by the movement of a UAV. We use the…
FAR: Fourier Aerial Video Recognition
Divya Kothandaraman, Tianrui Guan, Xijun Wang +3
We present an algorithm, Fourier Activity Recognition (FAR), for UAV video activity recognition. Our formulation uses a novel Fourier object disentanglement method to innately sepa…
METEOR:A Dense, Heterogeneous, and Unstructured Traffic Dataset With Rare Behaviors
Rohan Chandra, Xijun Wang, Mridul Mahajan +5
We present a new traffic dataset, METEOR, which captures traffic patterns and multi-agent driving behaviors in unstructured scenarios. METEOR consists of more than 1000 one-minute…
Dynamic Region-Aware Convolution
Jin Chen, Xijun Wang, Zichao Guo +2
We propose a new convolution called Dynamic Region-Aware Convolution (DRConv), which can automatically assign multiple filters to corresponding spatial regions where features have…
Fully Learnable Group Convolution for Acceleration of Deep Neural Networks
Xijun Wang, Meina Kan, Shiguang Shan +1
Benefitted from its great success on many tasks, deep learning is increasingly used on low-computational-cost devices, e.g. smartphone, embedded devices, etc. To reduce the high co…