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Found 18 papers, 7 papers with code
Consistent and Asymptotically Statistically-Efficient Solution to Camera Motion Estimation
Given 2D point correspondences between an image pair, inferring the camera motion is a fundamental issue in the computer vision community.
General Object Foundation Model for Images and Videos at Scale
We present GLEE in this work, an object-level foundation model for locating and identifying objects in images and videos.
Ranked #1 on
Referring Expression Segmentation
on Refer-YouTube-VOS (2021 public validation)
(using extra training data)
Long-tail Video Object Segmentation
Multi-Object Tracking
+8
Errors Dynamics in Affine Group Systems
In this paper, we focus on the error dynamics analysis for an affine group system under external disturbances or random noises.
InstMove: Instance Motion for Object-centric Video Segmentation
A common solution is to use optical flow to provide motion information, but essentially it only considers pixel-level motion, which still relies on appearance similarity and hence is often inaccurate under occlusion and fast movement.
Consistent and Asymptotically Efficient Localization from Range-Difference Measurements
Based on the preliminary consistent location estimate, a one-step GN iteration suffices to achieve the same asymptotic property as the ML estimator.
The Runner-up Solution for YouTube-VIS Long Video Challenge 2022
This technical report describes our 2nd-place solution for the ECCV 2022 YouTube-VIS Long Video Challenge.
On Embeddings and Inverse Embeddings of Input Design for Regularized System Identification
For the emerging regularized system identification, the study on input design has just started, and it is often formulated as a non-convex optimization problem that minimizes a scalar measure of the Bayesian mean squared error matrix subject to certain constraints, and the state-of-art method is the so-called quadratic mapping and inverse embedding (QMIE) method, where a time domain inverse embedding (TDIE) is proposed to find the inverse of the quadratic mapping.
CPnP: Consistent Pose Estimator for Perspective-n-Point Problem with Bias Elimination
The Perspective-n-Point (PnP) problem has been widely studied in both computer vision and photogrammetry societies.
Graph Distance Neural Networks for Predicting Multiple Drug Interactions
Based on our assumption, we convert the prediction of DDI to link prediction problem, utilizing known drug node characteristics and DDI types to predict unknown DDI types.
In Defense of Online Models for Video Instance Segmentation
In recent years, video instance segmentation (VIS) has been largely advanced by offline models, while online models gradually attracted less attention possibly due to their inferior performance.
Ranked #9 on
Video Instance Segmentation
on YouTube-VIS validation
(using extra training data)
Global and Asymptotically Efficient Localization from Range Measurements
In terms of whether the variance of measurement noises is known or not, we propose the Bias-Eli estimator (which involves solving a generalized trust region subproblem) and the Noise-Est estimator (which is obtained by solving a convex problem), respectively.
SeqFormer: Sequential Transformer for Video Instance Segmentation
Nevertheless, we observe that a stand-alone instance query suffices for capturing a time sequence of instances in a video, but attention mechanisms shall be done with each frame independently.
Ranked #2 on
Video Instance Segmentation
on HQ-YTVIS
Low-complexity Distributed Detection with One-bit Memory Under Neyman-Pearson Criterion
We consider a multi-stage distributed detection scenario, where $n$ sensors and a fusion center (FC) are deployed to accomplish a binary hypothesis test.
Event-Triggered Distributed Estimation With Decaying Communication Rate
We show that given the step size, adjusting the decay speed of the triggering threshold can lead to a tradeoff between the convergence rate of the estimation error and the decay speed of the communication rate.
Real-time tracking of COVID-19 and coronavirus research updates through text mining
The novel coronavirus (SARS-CoV-2) which causes COVID-19 is an ongoing pandemic.
ParaVS: A Simple, Fast, Efficient and Flexible Graph Neural Network Framework for Structure-Based Virtual Screening
However, the docking process can hardly be computationally efficient and accurate simultaneously because classic mechanics scoring function is used to approximate, but hardly reach, the quantum mechanics precision in this method.
Super-Resolution Domain Adaptation Networks for Semantic Segmentation via Pixel and Output Level Aligning
SRDA-Net can simultaneously achieve the super-resolution task and the domain adaptation task, thus satisfying the requirement of semantic segmentation for remote sensing images which usually involve various resolution images.
Learning Quadratic Games on Networks
Individuals, or organizations, cooperate with or compete against one another in a wide range of practical situations.
