551 citations · 791 across the 18 of their papers we have counts for
20 papers
EgoObjects: A Large-Scale Egocentric Dataset for Fine-Grained Object Understanding
Chenchen Zhu, Fanyi Xiao, Andres Alvarado +6
Object understanding in egocentric visual data is arguably a fundamental research topic in egocentric vision. However, existing object datasets are either non-egocentric or have li…
Exploring Open-Vocabulary Semantic Segmentation without Human Labels
Jun Chen, Deyao Zhu, Guocheng Qian +6
Semantic segmentation is a crucial task in computer vision that involves segmenting images into semantically meaningful regions at the pixel level. However, existing approaches oft…
Going Denser with Open-Vocabulary Part Segmentation
Peize Sun, Shoufa Chen, Chenchen Zhu +4
Object detection has been expanded from a limited number of categories to open vocabulary. Moving forward, a complete intelligent vision system requires understanding more fine-gra…
3rd Continual Learning Workshop Challenge on Egocentric Category and Instance Level Object Understanding
Lorenzo Pellegrini, Chenchen Zhu, Fanyi Xiao +7
Continual Learning, also known as Lifelong or Incremental Learning, has recently gained renewed interest among the Artificial Intelligence research community. Recent research effor…
SCVRL: Shuffled Contrastive Video Representation Learning
Michael Dorkenwald, Fanyi Xiao, Biagio Brattoli +2
We propose SCVRL, a novel contrastive-based framework for self-supervised learning for videos. Differently from previous contrast learning based methods that mostly focus on learni…
Hierarchical Self-supervised Representation Learning for Movie Understanding
Fanyi Xiao, Kaustav Kundu, Joseph Tighe +1
Most self-supervised video representation learning approaches focus on action recognition. In contrast, in this paper we focus on self-supervised video learning for movie understan…
MaCLR: Motion-aware Contrastive Learning of Representations for Videos
Fanyi Xiao, Joseph Tighe, Davide Modolo
We present MaCLR, a novel method to explicitly perform cross-modal self-supervised video representations learning from visual and motion modalities. Compared to previous video repr…
YolactEdge: Real-time Instance Segmentation on the Edge
Haotian Liu, Rafael A. Rivera Soto, Fanyi Xiao +1
We propose YolactEdge, the first competitive instance segmentation approach that runs on small edge devices at real-time speeds. Specifically, YolactEdge runs at up to 30.8 FPS on…
MARS: Mixed Virtual and Real Wearable Sensors for Human Activity Recognition with Multi-Domain Deep Learning Model
Ling Pei, Songpengcheng Xia, Lei Chu +4
Together with the rapid development of the Internet of Things (IoT), human activity recognition (HAR) using wearable Inertial Measurement Units (IMUs) becomes a promising technolog…
Delving Deeper into Anti-aliasing in ConvNets
Xueyan Zou, Fanyi Xiao, Zhiding Yu +1
Aliasing refers to the phenomenon that high frequency signals degenerate into completely different ones after sampling. It arises as a problem in the context of deep learning as do…
A Deep Learning Method for Complex Human Activity Recognition Using Virtual Wearable Sensors
Fanyi Xiao, Ling Pei, Lei Chu +4
Sensor-based human activity recognition (HAR) is now a research hotspot in multiple application areas. With the rise of smart wearable devices equipped with inertial measurement un…
Audiovisual SlowFast Networks for Video Recognition
Fanyi Xiao, Yong Jae Lee, Kristen Grauman +2
We present Audiovisual SlowFast Networks, an architecture for integrated audiovisual perception. AVSlowFast has Slow and Fast visual pathways that are deeply integrated with a Fast…
YOLACT++: Better Real-time Instance Segmentation
Daniel Bolya, Chong Zhou, Fanyi Xiao +1
We present a simple, fully-convolutional model for real-time (>30 fps) instance segmentation that achieves competitive results on MS COCO evaluated on a single Titan Xp, which is s…
STEP: Spatio-Temporal Progressive Learning for Video Action Detection
Xitong Yang, Xiaodong Yang, Ming-Yu Liu +3
In this paper, we propose Spatio-TEmporal Progressive (STEP) action detector---a progressive learning framework for spatio-temporal action detection in videos. Starting from a hand…
YOLACT: Real-time Instance Segmentation
Daniel Bolya, Chong Zhou, Fanyi Xiao +1
We present a simple, fully-convolutional model for real-time instance segmentation that achieves 29.8 mAP on MS COCO at 33.5 fps evaluated on a single Titan Xp, which is significan…
Video Object Detection with an Aligned Spatial-Temporal Memory
Fanyi Xiao, Yong Jae Lee
We introduce Spatial-Temporal Memory Networks for video object detection. At its core, a novel Spatial-Temporal Memory module (STMM) serves as the recurrent computation unit to mod…
Weakly-supervised Visual Grounding of Phrases with Linguistic Structures
Fanyi Xiao, Leonid Sigal, Yong Jae Lee
We propose a weakly-supervised approach that takes image-sentence pairs as input and learns to visually ground (i.e., localize) arbitrary linguistic phrases, in the form of spatial…
Who Will Share My Image? Predicting the Content Diffusion Path in Online Social Networks
Wenjian Hu, Krishna Kumar Singh, Fanyi Xiao +3
Content popularity prediction has been extensively studied due to its importance and interest for both users and hosts of social media sites like Facebook, Instagram, Twitter, and…
Track and Transfer: Watching Videos to Simulate Strong Human Supervision for Weakly-Supervised Object Detection
Krishna Kumar Singh, Fanyi Xiao, Yong Jae Lee
The status quo approach to training object detectors requires expensive bounding box annotations. Our framework takes a markedly different direction: we transfer tracked object box…
Multi-Task Regularization with Covariance Dictionary for Linear Classifiers
Fanyi Xiao, Ruikun Luo, Zhiding Yu
In this paper we propose a multi-task linear classifier learning problem called D-SVM (Dictionary SVM). D-SVM uses a dictionary of parameter covariance shared by all tasks to do mu…