119 citations · 373 across the 24 of their papers we have counts for
24 papers
Neural Interactive Keypoint Detection
Jie Yang, Ailing Zeng, Feng Li +3
This work proposes an end-to-end neural interactive keypoint detection framework named Click-Pose, which can significantly reduce more than 10 times labeling costs of 2D keypoint a…
IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
Hu Ye, Jun Zhang, Sibo Liu +2
Recent years have witnessed the strong power of large text-to-image diffusion models for the impressive generative capability to create high-fidelity images. However, it is very tr…
A Unified Interactive Model Evaluation for Classification, Object Detection, and Instance Segmentation in Computer Vision
Changjian Chen, Yukai Guo, Fengyuan Tian +7
Existing model evaluation tools mainly focus on evaluating classification models, leaving a gap in evaluating more complex models, such as object detection. In this paper, we devel…
Semantic-SAM: Segment and Recognize Anything at Any Granularity
Feng Li, Hao Zhang, Peize Sun +6
In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advanta…
detrex: Benchmarking Detection Transformers
Tianhe Ren, Shilong Liu, Feng Li +13
The DEtection TRansformer (DETR) algorithm has received considerable attention in the research community and is gradually emerging as a mainstream approach for object detection and…
Unconventional ferroelectric domain switching dynamics in CuInP2S6 from first principles
Ri He, Hua Wang, Fucai Liu +3
The switching dynamics of ferroelectric materials is a crucial intrinsic property which directly affects the operation and performance of ferroelectric devices. In conventional fer…
A Strong and Reproducible Object Detector with Only Public Datasets
Tianhe Ren, Jianwei Yang, Shilong Liu +6
This work presents Focal-Stable-DINO, a strong and reproducible object detection model which achieves 64.6 AP on COCO val2017 and 64.8 AP on COCO test-dev using only 700M parameter…
PREIM3D: 3D Consistent Precise Image Attribute Editing from a Single Image
Jianhui Li, Jianmin Li, Haoji Zhang +5
We study the 3D-aware image attribute editing problem in this paper, which has wide applications in practice. Recent methods solved the problem by training a shared encoder to map…
Towards an Understanding and Explanation for Mixed-Initiative Artificial Scientific Text Detection
Luoxuan Weng, Minfeng Zhu, Kam Kwai Wong +5
Large language models (LLMs) have gained popularity in various fields for their exceptional capability of generating human-like text. Their potential misuse has raised social conce…
Detection Transformer with Stable Matching
Shilong Liu, Tianhe Ren, Jiayu Chen +8
This paper is concerned with the matching stability problem across different decoder layers in DEtection TRansformers (DETR). We point out that the unstable matching in DETR is cau…
A Simple Framework for Open-Vocabulary Segmentation and Detection
Hao Zhang, Feng Li, Xueyan Zou +5
We present OpenSeeD, a simple Open-vocabulary Segmentation and Detection framework that jointly learns from different segmentation and detection datasets. To bridge the gap of voca…
MP-Former: Mask-Piloted Transformer for Image Segmentation
Hao Zhang, Feng Li, Huaizhe Xu +4
We present a mask-piloted Transformer which improves masked-attention in Mask2Former for image segmentation. The improvement is based on our observation that Mask2Former suffers fr…
Lite DETR : An Interleaved Multi-Scale Encoder for Efficient DETR
Feng Li, Ailing Zeng, Shilong Liu +4
Recent DEtection TRansformer-based (DETR) models have obtained remarkable performance. Its success cannot be achieved without the re-introduction of multi-scale feature fusion in t…
Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation
Jie Yang, Ailing Zeng, Shilong Liu +3
This paper presents a novel end-to-end framework with Explicit box Detection for multi-person Pose estimation, called ED-Pose, where it unifies the contextual learning between huma…
Introducing Depth into Transformer-based 3D Object Detection
Hao Zhang, Hongyang Li, Ailing Zeng +4
In this paper, we present DAT, a Depth-Aware Transformer framework designed for camera-based 3D detection. Our model is based on observing two major issues in existing methods: lar…
XNLI: Explaining and Diagnosing NLI-based Visual Data Analysis
Yingchaojie Feng, Xingbo Wang, Bo Pan +7
Natural language interfaces (NLIs) enable users to flexibly specify analytical intentions in data visualization. However, diagnosing the visualization results without understanding…
Shift current response in elemental two-dimensional ferroelectrics
Zhuang Qian, Jian Zhou, Hua Wang +1
A bulk material without inversion symmetry can generate a direct current under illumination. This interface-free current generation mechanism, referred to as the bulk photovoltaic…
DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding
Shilong Liu, Yaoyuan Liang, Feng Li +5
In this paper, we study the problem of visual grounding by considering both phrase extraction and grounding (PEG). In contrast to the previous phrase-known-at-test setting, PEG req…
A Unified Mutual Supervision Framework for Referring Expression Segmentation and Generation
Shijia Huang, Feng Li, Hao Zhang +3
Reference Expression Segmentation (RES) and Reference Expression Generation (REG) are mutually inverse tasks that can be naturally jointly trained. Though recent work has explored…
Robust analyses for longitudinal clinical trials with missing and non-normal continuous outcomes
Siyi Liu, Yilong Zhang, Gregory T Golm +3
Missing data is unavoidable in longitudinal clinical trials, and outcomes are not always normally distributed. In the presence of outliers or heavy-tailed distributions, the conven…
Multiply robust estimators in longitudinal studies with missing data under control-based imputation
Siyi Liu, Shu Yang, Yilong Zhang +2
Longitudinal studies are often subject to missing data. The ICH E9(R1) addendum addresses the importance of defining a treatment effect estimand with the consideration of intercurr…
Learnable Embedding Sizes for Recommender Systems
Siyi Liu, Chen Gao, Yihong Chen +2
The embedding-based representation learning is commonly used in deep learning recommendation models to map the raw sparse features to dense vectors. The traditional embedding manne…
Long-tail Session-based Recommendation
Siyi Liu, Yujia Zheng
Session-based recommendation focuses on the prediction of user actions based on anonymous sessions and is a necessary method in the lack of user historical data. However, none of t…
Balancing Multi-level Interactions for Session-based Recommendation
Yujia Zheng, Siyi Liu, Zailei Zhou
Predicting user actions based on anonymous sessions is a challenge to general recommendation systems because the lack of user profiles heavily limits data-driven models. Recently,…