no code implementations • 8 Sep 2023 • Li Liu, Da Chen, Minglei Shu, Laurent D. Cohen
These boundary proposals are then incorporated into the proposed image segmentation model, such that the target segmentation contours are made up of a set of selected boundary proposals and the corresponding geodesic paths linking them.
1 code implementation • ICCV 2023 • Chaorui Deng, Qi Chen, Pengda Qin, Da Chen, Qi Wu
In text-video retrieval, recent works have benefited from the powerful learning capabilities of pre-trained text-image foundation models (e. g., CLIP) by adapting them to the video domain.
1 code implementation • ICCV 2023 • Chaorui Deng, Da Chen, Qi Wu
In Video Object Detection (VID), a common practice is to leverage the rich temporal contexts from the video to enhance the object representations in each frame.
1 code implementation • ICCV 2023 • Xiaofeng Mao, Yuefeng Chen, Yao Zhu, Da Chen, Hang Su, Rong Zhang, Hui Xue
To give a more comprehensive robustness assessment, we introduce COCO-O(ut-of-distribution), a test dataset based on COCO with 6 types of natural distribution shifts.
no code implementations • ICCV 2023 • Aming Wu, Da Chen, Cheng Deng
For this task, the challenge mainly lies in how to only leverage the known in-distribution (ID) data to detect OOD objects accurately without affecting the detection of ID objects, which can be framed as the diffusion problem for deep feature synthesis.
no code implementations • 2 Nov 2022 • Da Chen, Nima Emami, Shahed Rezaei, Philipp L. Rosendahl, Bai-Xiang Xu, Jens Schneider, Kang Gao, Jie Yang
The error range of CNN models leads to an uncertain mechanical performance, which is further evaluated in a structural uncertainty analysis on the FG porous three-layer beam consisting of two thin high-density layers and a thick low-density one, where the imprecise CNN predicted moduli are represented as triangular fuzzy numbers in double parametric form.
no code implementations • 1 Sep 2022 • Da Chen, Shan-Guo Feng, Hua-Hua Wang, Jia-Ning Cao, Zhi-Wei Zhang, Zhi-Xin Yang, Ao Yan, Lu Gao, Ze Zhang
The nature of multiple samples to extract correlation information limits the applications of ghost imaging of moving objects.
no code implementations • 1 Nov 2021 • Da Chen, Jean-Marie Mirebeau, Minglei Shu, Xuecheng Tai, Laurent D. Cohen
The minimal geodesic models based on the Eikonal equations are capable of finding suitable solutions in various image segmentation scenarios.
no code implementations • CVPR 2021 • Chaorui Deng, ShiZhe Chen, Da Chen, Yuan He, Qi Wu
The dense video captioning task aims to detect and describe a sequence of events in a video for detailed and coherent storytelling.
no code implementations • ICCV 2021 • Yassir Saquil, Da Chen, Yuan He, Chuan Li, Yong-Liang Yang
In this paper, we investigate video summarization in the supervised setting.
no code implementations • ICCV 2021 • Da Chen, Laurent D. Cohen, Jean-Marie Mirebeau, Xue-Cheng Tai
The minimal geodesic models based on the Eikonal equations are capable of finding suitable solutions in various image segmentation scenarios.
no code implementations • 16 Aug 2020 • Da Chen, Jian Zhu, Xinxin Zhang, Ming-Lei Shu, Laurent D. Cohen
Minimal paths are regarded as a powerful and efficient tool for boundary detection and image segmentation due to its global optimality and the well-established numerical solutions such as fast marching method.
no code implementations • 14 Jun 2020 • Da Chen, Jack Spencer, Jean-Marie Mirebeau, Ke Chen, Minglei Shu, Laurent D. Cohen
The Voronoi diagram-based dual-front active contour models are known as a powerful and efficient way for addressing the image segmentation and domain partitioning problems.
no code implementations • 8 Mar 2020 • Li Liu, Da Chen, Ming-Lei Shu, Baosheng Li, Huazhong Shu, Michel Paques, Laurent D. Cohen
Tubular structure tracking is a crucial task in the fields of computer vision and medical image analysis.
3 code implementations • 23 Dec 2019 • Gongfan Fang, Jie Song, Chengchao Shen, Xinchao Wang, Da Chen, Mingli Song
Knowledge Distillation (KD) has made remarkable progress in the last few years and become a popular paradigm for model compression and knowledge transfer.
no code implementations • 20 Dec 2019 • Da Chen, Jean-Marie Mirebeau, Huazhong Shu, Laurent D. Cohen
In this paper, we introduce a new variational image segmentation model based on the minimal geodesic path framework and the eikonal PDE, where the region-based appearance term that defines then regional homogeneity features can be taken into account for estimating the associated minimal geodesic paths.
no code implementations • 18 Dec 2019 • Da Chen, Yong-Liang Yang, Zunlei Feng, Xiang Wu, Mingli Song, Wenbin Li, Yuan He, Hui Xue, Feng Mao
This strategy leads to severe meta shift issues across multiple tasks, meaning the learned prototypes or class descriptors are not stable as each task only involves their own support set.
2 code implementations • 14 Nov 2019 • Da Chen, Yuefeng Chen, Yuhong Li, Feng Mao, Yuan He, Hui Xue
In this paper, we proposed to train a more generalized embedding network with self-supervised learning (SSL) which can provide robust representation for downstream tasks by learning from the data itself.
Ranked #4 on Few-Shot Image Classification on Mini-ImageNet - 1-Shot Learning (using extra training data)
no code implementations • 23 Jul 2019 • Da Chen, Laurent D. Cohen
In this chapter, we give an overview of part of our previous work based on the minimal path framework and the Eikonal partial differential equation (PDE).
no code implementations • 20 Jan 2019 • Shipeng Xie, Da Chen, Rong Zhang, Hui Xue
Deep neural network models have recently draw lots of attention, as it consistently produce impressive results in many computer vision tasks such as image classification, object detection, etc.
no code implementations • 21 Sep 2018 • Da Chen, Jiong Zhang, Laurent D. Cohen
In this paper, we propose a new minimal path model associated with a dynamic Riemannian metric embedded with an appearance feature coherence penalty and an adaptive anisotropy enhancement term.
no code implementations • 17 Oct 2017 • Da Chen, Laurent D. Cohen
In this paper, we propose a new minimal path model for minimally interactive retinal vessel centerline extraction.
no code implementations • 19 Apr 2017 • Wenbin Li, Da Chen, Zhihan Lv, Yan Yan, Darren Cosker
It is difficult to recover the motion field from a real-world footage given a mixture of camera shake and other photometric effects.
no code implementations • 1 Dec 2016 • Da Chen, Jean-Marie Mirebeau, Laurent D. Cohen
In this paper, we propose a novel curvature-penalized minimal path model via an orientation-lifted Finsler metric and the Euler elastica curve.
no code implementations • 7 Sep 2016 • Da Chen, Wenbin Li, Peter Hall
We propose an algorithm for dense motion estimation of smoke.
no code implementations • CVPR 2016 • Da Chen, Jean-Marie Mirebeau, Laurent D. Cohen
This metric is non-Riemannian and asymmetric, defined on an orientation lifted space, incorporating the curvature penalty in the geodesic energy.