Search Results for author:
Found 18 papers, 12 papers with code
RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution
As a fundamental challenge in visual computing, video super-resolution (VSR) focuses on reconstructing highdefinition video sequences from their degraded lowresolution counterparts.
Motion Anything: Any to Motion Generation
Conditional motion generation has been extensively studied in computer vision, yet two critical challenges remain.
Ranked #1 on
Motion Synthesis
on TMD
Foundations and Recent Trends in Multimodal Mobile Agents: A Survey
This survey provides a comprehensive review of mobile agent technologies, focusing on recent advancements that enhance real-time adaptability and multimodal interaction.
MMCLIP: Cross-modal Attention Masked Modelling for Medical Language-Image Pre-Training
To this end, this paper proposes the MMCLIP (Masked Medical Contrastive Language-Image Pre-Training) framework to enhance pathological learning and feature learning via unpaired data.
Semi-supervised Video Semantic Segmentation Using Unreliable Pseudo Labels for PVUW2024
Pixel-level Scene Understanding is one of the fundamental problems in computer vision, which aims at recognizing object classes, masks and semantics of each pixel in the given image.
2nd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation
In order to deal with the task of video panoptic segmentation in the wild, we propose a robust integrated video panoptic segmentation solution.
Motion Avatar: Generate Human and Animal Avatars with Arbitrary Motion
Firstly, we proposed a novel agent-based approach named Motion Avatar, which allows for the automatic generation of high-quality customizable human and animal avatars with motions through text queries.
Real-Time 4K Super-Resolution of Compressed AVIF Images. AIS 2024 Challenge Survey
This paper introduces a novel benchmark as part of the AIS 2024 Real-Time Image Super-Resolution (RTSR) Challenge, which aims to upscale compressed images from 540p to 4K resolution (4x factor) in real-time on commercial GPUs.
I Learn Better If You Speak My Language: Understanding the Superior Performance of Fine-Tuning Large Language Models with LLM-Generated Responses
This paper explores an intriguing observation: fine-tuning a large language model (LLM) with responses generated by a LLM often yields better results than using responses generated by humans, particularly in reasoning tasks.
SegReg: Segmenting OARs by Registering MR Images and CT Annotations
This manual process is highly time-consuming and expensive, limiting the number of patients who can receive timely radiotherapy.
IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers
Data augmentation has been proven effective for training high-accuracy convolutional neural network classifiers by preventing overfitting.
From Zero to Hero: Detecting Leaked Data through Synthetic Data Injection and Model Querying
In this paper, we concentrate on the domain of tabular data and introduce a novel methodology, Local Distribution Shifting Synthesis (\textsc{LDSS}), to detect leaked data that are used to train classification models.
BHSD: A 3D Multi-Class Brain Hemorrhage Segmentation Dataset
Intracranial hemorrhage (ICH) is a pathological condition characterized by bleeding inside the skull or brain, which can be attributed to various factors.
Recyclable Semi-supervised Method Based on Multi-model Ensemble for Video Scene Parsing
Pixel-level Scene Understanding is one of the fundamental problems in computer vision, which aims at recognizing object classes, masks and semantics of each pixel in the given image.
Act Like a Radiologist: Radiology Report Generation across Anatomical Regions
To address these issues, we propose X-RGen, a radiologist-minded report generation framework across six anatomical regions.
Ranked #1 on
Medical Report Generation
on IU X-Ray
(using extra training data)
Power Efficient Video Super-Resolution on Mobile NPUs with Deep Learning, Mobile AI & AIM 2022 challenge: Report
While numerous solutions have been proposed for this problem, they are usually quite computationally demanding, demonstrating low FPS rates and power efficiency on mobile devices.
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
This challenge includes three tracks.
Physical Distance Between Quantum States
We propose a physical distance between two quantum states.
Quantum Physics
