794 citations · 1.1k across the 24 of their papers we have counts for
24 papers
UniPAR: A Unified Framework for Pedestrian Attribute Recognition
Minghe Xu, Rouying Wu, Jiarui Xu +5
Pedestrian Attribute Recognition is a foundational computer vision task that provides essential support for downstream applications, including person retrieval in video surveillanc…
Decoupling Amplitude and Phase Attention in Frequency Domain for RGB-Event based Visual Object Tracking
Shiao Wang, Xiao Wang, Haonan Zhao +6
Existing RGB-Event visual object tracking approaches primarily rely on conventional feature-level fusion, failing to fully exploit the unique advantages of event cameras. In partic…
One-Minute Video Generation with Test-Time Training
Karan Dalal, Daniel Koceja, Gashon Hussein +12
Transformers today still struggle to generate one-minute videos because self-attention layers are inefficient for long context. Alternatives such as Mamba layers struggle with comp…
LoRA-TTT: Low-Rank Test-Time Training for Vision-Language Models
Yuto Kojima, Jiarui Xu, Xueyan Zou +1
The rapid advancements in vision-language models (VLMs), such as CLIP, have intensified the need to address distribution shifts between training and testing datasets. Although prio…
Parallel Sequence Modeling via Generalized Spatial Propagation Network
Hongjun Wang, Wonmin Byeon, Jiarui Xu +6
We present the Generalized Spatial Propagation Network (GSPN), a new attention mechanism optimized for vision tasks that inherently captures 2D spatial structures. Existing attenti…
HandsOnVLM: Vision-Language Models for Hand-Object Interaction Prediction
Chen Bao, Jiarui Xu, Xiaolong Wang +2
How can we predict future interaction trajectories of human hands in a scene given high-level colloquial task specifications in the form of natural language? In this paper, we exte…
Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Yu Sun, Xinhao Li, Karan Dalal +9
Self-attention performs well in long context but has quadratic complexity. Existing RNN layers have linear complexity, but their performance in long context is limited by the expre…
Pixel Aligned Language Models
Jiarui Xu, Xingyi Zhou, Shen Yan +5
Large language models have achieved great success in recent years, so as their variants in vision. Existing vision-language models can describe images in natural languages, answer…
IMProv: Inpainting-based Multimodal Prompting for Computer Vision Tasks
Jiarui Xu, Yossi Gandelsman, Amir Bar +4
In-context learning allows adapting a model to new tasks given a task description at test time. In this paper, we present IMProv - a generative model that is able to in-context lea…
Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models
Jiarui Xu, Sifei Liu, Arash Vahdat +3
We present ODISE: Open-vocabulary DIffusion-based panoptic SEgmentation, which unifies pre-trained text-image diffusion and discriminative models to perform open-vocabulary panopti…
GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation
Chenhongyi Yang, Jiarui Xu, Shalini De Mello +2
We present the Group Propagation Vision Transformer (GPViT): a novel nonhierarchical (i.e. non-pyramidal) transformer model designed for general visual recognition with high-resolu…
Learning Implicit Feature Alignment Function for Semantic Segmentation
Hanzhe Hu, Yinbo Chen, Jiarui Xu +4
Integrating high-level context information with low-level details is of central importance in semantic segmentation. Towards this end, most existing segmentation models apply bilin…
GroupViT: Semantic Segmentation Emerges from Text Supervision
Jiarui Xu, Shalini De Mello, Sifei Liu +4
Grouping and recognition are important components of visual scene understanding, e.g., for object detection and semantic segmentation. With end-to-end deep learning systems, groupi…
Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time
Shaowei Liu, Hanwen Jiang, Jiarui Xu +2
Estimating 3D hand and object pose from a single image is an extremely challenging problem: hands and objects are often self-occluded during interactions, and the 3D annotations ar…
Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective
Jiarui Xu, Xiaolong Wang
Learning a good representation for space-time correspondence is the key for various computer vision tasks, including tracking object bounding boxes and performing video object pixe…
Global Context Networks
Yue Cao, Jiarui Xu, Stephen Lin +2
The Non-Local Network (NLNet) presents a pioneering approach for capturing long-range dependencies within an image, via aggregating query-specific global context to each query posi…
DRG: Dual Relation Graph for Human-Object Interaction Detection
Chen Gao, Jiarui Xu, Yuliang Zou +1
We tackle the challenging problem of human-object interaction (HOI) detection. Existing methods either recognize the interaction of each human-object pair in isolation or perform j…
Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching
Xuhua Huang, Jiarui Xu, Yu-Wing Tai +1
Significant progress has been made in Video Object Segmentation (VOS), the video object tracking task in its finest level. While the VOS task can be naturally decoupled into image…
Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories
Tiange Luo, Kaichun Mo, Zhiao Huang +4
We address the problem of discovering 3D parts for objects in unseen categories. Being able to learn the geometry prior of parts and transfer this prior to unseen categories pose f…
MMDetection: Open MMLab Detection Toolbox and Benchmark
Kai Chen, Jiaqi Wang, Jiangmiao Pang +22
We present MMDetection, an object detection toolbox that contains a rich set of object detection and instance segmentation methods as well as related components and modules. The to…
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
Yue Cao, Jiarui Xu, Stephen Lin +2
The Non-Local Network (NLNet) presents a pioneering approach for capturing long-range dependencies, via aggregating query-specific global context to each query position. However, t…
Spatial-Temporal Relation Networks for Multi-Object Tracking
Jiarui Xu, Yue Cao, Zheng Zhang +1
Recent progress in multiple object tracking (MOT) has shown that a robust similarity score is key to the success of trackers. A good similarity score is expected to reflect multipl…
Deep High Dynamic Range Imaging with Large Foreground Motions
Shangzhe Wu, Jiarui Xu, Yu-Wing Tai +1
This paper proposes the first non-flow-based deep framework for high dynamic range (HDR) imaging of dynamic scenes with large-scale foreground motions. In state-of-the-art deep HDR…
Demonstrating research subcommunities in mathematical networks
Steven B. Bradlow, Konstantinos Kapenekakis, Georgios Kydonakis +2
We propose a method for demonstrating sub community structure in scientific networks of relatively small size from analyzing databases of publications. Research relationships betwe…