Search Results for author: Da Chen

Found 26 papers, 5 papers with code

Grouping Boundary Proposals for Fast Interactive Image Segmentation

no code implementations8 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.

Image Segmentation Segmentation +1

Prompt Switch: Efficient CLIP Adaptation for Text-Video Retrieval

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.

Retrieval Video Captioning +1

Identity-Consistent Aggregation for Video Object Detection

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.

Object object-detection +1

COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts

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.

Autonomous Driving Object +2

Deep Feature Deblurring Diffusion for Detecting Out-of-Distribution Objects

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.

Deblurring object-detection +1

AI enhanced finite element multiscale modelling and structural uncertainty analysis of a functionally graded porous beam

no code implementations2 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.

Group frame neural network of moving object ghost imaging combined with frame merging algorithm

no code implementations1 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.

Geodesic Models with Convexity Shape Prior

no code implementations1 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.

Image Segmentation Segmentation +1

Sketch, Ground, and Refine: Top-Down Dense Video Captioning

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.

Dense Video Captioning Sentence

An Elastica Geodesic Approach With Convexity Shape Prior

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.

Image Segmentation Segmentation +1

Geodesic Paths for Image Segmentation with Implicit Region-based Homogeneity Enhancement

no code implementations16 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.

Boundary Detection Image Segmentation +2

A Generalized Asymmetric Dual-front Model for Active Contours and Image Segmentation

no code implementations14 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.

Image Segmentation Semantic Segmentation

Trajectory Grouping with Curvature Regularization for Tubular Structure Tracking

no code implementations8 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.

Data-Free Adversarial Distillation

3 code implementations23 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.

Knowledge Distillation Model Compression +2

A Region-based Randers Geodesic Approach for Image Segmentation

no code implementations20 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.

Boundary Detection Image Segmentation +2

Semantic Regularization: Improve Few-shot Image Classification by Reducing Meta Shift

no code implementations18 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.

Few-Shot Image Classification General Classification +1

Self-Supervised Learning For Few-Shot Image Classification

2 code implementations14 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.

Classification cross-domain few-shot learning +3

From Active Contours to Minimal Geodesic Paths: New Solutions to Active Contours Problems by Eikonal Equations

no code implementations23 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).

Boundary Detection Image Segmentation +1

Deep Features Analysis with Attention Networks

no code implementations20 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.

Classification General Classification +3

Minimal Paths for Tubular Structure Segmentation with Coherence Penalty and Adaptive Anisotropy

no code implementations21 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.

A New Coherence-Penalized Minimal Path Model with Application to Retinal Vessel Centerline Delineation

no code implementations17 Oct 2017 Da Chen, Laurent D. Cohen

In this paper, we propose a new minimal path model for minimally interactive retinal vessel centerline extraction.

Learn to Model Motion from Blurry Footages

no code implementations19 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.

Optical Flow Estimation

Global Minimum for a Finsler Elastica Minimal Path Approach

no code implementations1 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.

Contour Detection

Dense Motion Estimation for Smoke

no code implementations7 Sep 2016 Da Chen, Wenbin Li, Peter Hall

We propose an algorithm for dense motion estimation of smoke.

Motion Estimation

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