119 citations · 373 across the 24 of their papers we have counts for
15 papers · 1 filter
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…
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…
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…
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…