794 citations · 1.2k across the 30 of their papers we have counts for
30 papers
Rethinking Amodal Video Segmentation from Learning Supervised Signals with Object-centric Representation
Ke Fan, Jingshi Lei, Xuelin Qian +5
Video amodal segmentation is a particularly challenging task in computer vision, which requires to deduce the full shape of an object from the visible parts of it. Recently, some s…
Partition-A-Medical-Image: Extracting Multiple Representative Sub-regions for Few-shot Medical Image Segmentation
Yazhou Zhu, Shidong Wang, Tong Xin +2
Few-shot Medical Image Segmentation (FSMIS) is a more promising solution for medical image segmentation tasks where high-quality annotations are naturally scarce. However, current…
Object-Centric Multiple Object Tracking
Zixu Zhao, Jiaze Wang, Max Horn +13
Unsupervised object-centric learning methods allow the partitioning of scenes into entities without additional localization information and are excellent candidates for reducing th…
Unsupervised Open-Vocabulary Object Localization in Videos
Ke Fan, Zechen Bai, Tianjun Xiao +11
In this paper, we show that recent advances in video representation learning and pre-trained vision-language models allow for substantial improvements in self-supervised video obje…
FLM-101B: An Open LLM and How to Train It with $100K Budget
Xiang Li, Yiqun Yao, Xin Jiang +10
Large language models (LLMs) are considered important approaches towards foundational machine intelligence, achieving remarkable success in Natural Language Processing and multimod…
Optical flow-based vascular respiratory motion compensation
Keke Yang, Zheng Zhang, Meng Li +3
This paper develops a new vascular respiratory motion compensation algorithm, Motion-Related Compensation (MRC), to conduct vascular respiratory motion compensation by extrapolatin…
Local-Global Pseudo-label Correction for Source-free Domain Adaptive Medical Image Segmentation
Yanyu Ye, Zhengxi Zhang, Chunna Tianb +1
Domain shift is a commonly encountered issue in medical imaging solutions, primarily caused by variations in imaging devices and data sources. To mitigate this problem, unsupervise…
Masked Structural Growth for 2x Faster Language Model Pre-training
Yiqun Yao, Zheng Zhang, Jing Li +1
Accelerating large language model pre-training is a critical issue in present research. In this paper, we focus on speeding up pre-training by progressively growing from a small Tr…
Bridging the Gap to Real-World Object-Centric Learning
Maximilian Seitzer, Max Horn, Andrii Zadaianchuk +8
Humans naturally decompose their environment into entities at the appropriate level of abstraction to act in the world. Allowing machine learning algorithms to derive this decompos…
A Survey on Incomplete Multi-view Clustering
Jie Wen, Zheng Zhang, Lunke Fei +4
Conventional multi-view clustering seeks to partition data into respective groups based on the assumption that all views are fully observed. However, in practical applications, suc…
End-to-end contextual asr based on posterior distribution adaptation for hybrid ctc/attention system
Zhengyi Zhang, Pan Zhou
End-to-end (E2E) speech recognition architectures assemble all components of traditional speech recognition system into a single model. Although it simplifies ASR system, it introd…
Online, Informative MCMC Thinning with Kernelized Stein Discrepancy
Cole Hawkins, Alec Koppel, Zheng Zhang
A fundamental challenge in Bayesian inference is efficient representation of a target distribution. Many non-parametric approaches do so by sampling a large number of points using…
A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict
Yiyi Liu, Yequan Wang, Aixin Sun +3
Sarcasm employs ambivalence, where one says something positive but actually means negative, and vice versa. The essence of sarcasm, which is also a sufficient and necessary conditi…
Context-Aware Attention-Based Data Augmentation for POI Recommendation
Yang Li, Yadan Luo, Zheng Zhang +2
With the rapid growth of location-based social networks (LBSNs), Point-Of-Interest (POI) recommendation has been broadly studied in this decade. Recently, the next POI recommendati…
Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition
Zhao Zhang, Zemin Tang, Zheng Zhang +3
The Deep Convolutional Neural Networks (CNNs) have obtained a great success for pattern recognition, such as recognizing the texts in images. But existing CNNs based frameworks sti…
Deep Self-representative Concept Factorization Network for Representation Learning
Yan Zhang, Zhao Zhang, Zheng Zhang +4
In this paper, we investigate the unsupervised deep representation learning issue and technically propose a novel framework called Deep Self-representative Concept Factorization Ne…
Compressed DenseNet for Lightweight Character Recognition
Zhao Zhang, Zemin Tang, Yang Wang +3
Convolutional Recurrent Neural Network (CRNN) is a popular network for recognizing texts in images. Advances like the variant of CRNN, such as Dense Convolutional Network with Conn…
Discriminative Local Sparse Representation by Robust Adaptive Dictionary Pair Learning
Yulin Sun, Zhao Zhang, Weiming Jiang +4
In this paper, we propose a structured Robust Adaptive Dic-tionary Pair Learning (RA-DPL) framework for the discrim-inative sparse representation learning. To achieve powerful repr…
Stochastic Model Predictive Control of Autonomous Systems with Non-Gaussian Correlated Uncertainty
Huishan Chen, Zheng Zhang
Many systems such as autonomous vehicles and quadrotors are subject to parametric uncertainties and external disturbances. These uncertainties can lead to undesired performance deg…
Adaptive Structure-constrained Robust Latent Low-Rank Coding for Image Recovery
Zhao Zhang, Lei Wang, Sheng Li +4
In this paper, we propose a robust representation learning model called Adaptive Structure-constrained Low-Rank Coding (AS-LRC) for the latent representation of data. To recover th…
Learning Structured Twin-Incoherent Twin-Projective Latent Dictionary Pairs for Classification
Zhao Zhang, Yulin Sun, Zheng Zhang +3
In this paper, we extend the popular dictionary pair learning (DPL) into the scenario of twin-projective latent flexible DPL under a structured twin-incoherence. Technically, a nov…
MMDetection: Open MMLab Detection Toolbox and Benchmark
Kai Chen, Jiaqi Wang, Jiangmiao Pang +22
We present MMDetection, an object detection toolbox that contains a rich set of object detection and instance segmentation methods as well as related components and modules. The to…
Joint Subspace Recovery and Enhanced Locality Driven Robust Flexible Discriminative Dictionary Learning
Zhao Zhang, Jiahuan Ren, Weiming Jiang +4
We propose a joint subspace recovery and enhanced locality based robust flexible label consistent dictionary learning method called Robust Flexible Discriminative Dictionary Learni…
Star-Transformer
Qipeng Guo, Xipeng Qiu, Pengfei Liu +3
Although Transformer has achieved great successes on many NLP tasks, its heavy structure with fully-connected attention connections leads to dependencies on large training data. In…