activity
20172024
most citedEnd-to-End Video Instance Segmentation with Transformers

65 citations · 270 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2024

Unleashing the Potential of the Diffusion Model in Few-shot Semantic Segmentation

Muzhi Zhu, Yang Liu, Zekai Luo +5

The Diffusion Model has not only garnered noteworthy achievements in the realm of image generation but has also demonstrated its potential as an effective pretraining method utiliz…

cs.CV2024★ 2 cited

A Simple Image Segmentation Framework via In-Context Examples

Yang Liu, Chenchen Jing, Hengtao Li +4

Recently, there have been explorations of generalist segmentation models that can effectively tackle a variety of image segmentation tasks within a unified in-context learning fram…

cs.CV2021★ 1 cited

SOLO: A Simple Framework for Instance Segmentation

Xinlong Wang, Rufeng Zhang, Chunhua Shen +2

Compared to many other dense prediction tasks, e.g., semantic segmentation, it is the arbitrary number of instances that has made instance segmentation much more challenging. In or…

cs.CV2021★ 2 cited

FCPose: Fully Convolutional Multi-Person Pose Estimation with Dynamic Instance-Aware Convolutions

Weian Mao, Zhi Tian, Xinlong Wang +1

We propose a fully convolutional multi-person pose estimation framework using dynamic instance-aware convolutions, termed FCPose. Different from existing methods, which often requi…

cs.CV2021★ 57 cited

TFPose: Direct Human Pose Estimation with Transformers

Weian Mao, Yongtao Ge, Chunhua Shen +3

We propose a human pose estimation framework that solves the task in the regression-based fashion. Unlike previous regression-based methods, which often fall behind those state-of-…

cs.CV2020★ 4 cited

Diverse Knowledge Distillation for End-to-End Person Search

Xinyu Zhang, Xinlong Wang, Jia-Wang Bian +2

Person search aims to localize and identify a specific person from a gallery of images. Recent methods can be categorized into two groups, i.e., two-step and end-to-end approaches.…

cs.CV2020★ 28 cited

BoxInst: High-Performance Instance Segmentation with Box Annotations

Zhi Tian, Chunhua Shen, Xinlong Wang +1

We present a high-performance method that can achieve mask-level instance segmentation with only bounding-box annotations for training. While this setting has been studied in the l…

cs.CV2020★ 65 cited

End-to-End Video Instance Segmentation with Transformers

Yuqing Wang, Zhaoliang Xu, Xinlong Wang +4

Video instance segmentation (VIS) is the task that requires simultaneously classifying, segmenting and tracking object instances of interest in video. Recent methods typically deve…

cs.CV2020★ 40 cited

Dense Contrastive Learning for Self-Supervised Visual Pre-Training

Xinlong Wang, Rufeng Zhang, Chunhua Shen +2

To date, most existing self-supervised learning methods are designed and optimized for image classification. These pre-trained models can be sub-optimal for dense prediction tasks…

cs.CV2019★ 34 cited

Associatively Segmenting Instances and Semantics in Point Clouds

Xinlong Wang, Shu Liu, Xiaoyong Shen +2

A 3D point cloud describes the real scene precisely and intuitively.To date how to segment diversified elements in such an informative 3D scene is rarely discussed. In this paper,…

cs.CV2017★ 37 cited

Adversarial Generation of Training Examples: Applications to Moving Vehicle License Plate Recognition

Xinlong Wang, Zhipeng Man, Mingyu You +1

Generative Adversarial Networks (GAN) have attracted much research attention recently, leading to impressive results for natural image generation. However, to date little success w…