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Found 25 papers, 9 papers with code
Self-reconfiguration Strategies for Space-distributed Spacecraft
The joint planning of the robotic arm is then accomplished through forward and reverse kinematics.
AsynEIO: Asynchronous Monocular Event-Inertial Odometry Using Gaussian Process Regression
Event cameras, when combined with inertial sensors, show significant potential for motion estimation in challenging scenarios, such as high-speed maneuvers and low-light environments.
Large Language Models Might Not Care What You Are Saying: Prompt Format Beats Descriptions
With the help of in-context learning (ICL), large language models (LLMs) have achieved impressive performance across various tasks.
SCOI: Syntax-augmented Coverage-based In-context Example Selection for Machine Translation
In-context learning (ICL) greatly improves the performance of large language models (LLMs) on various down-stream tasks, where the improvement highly depends on the quality of demonstrations.
Matting by Generation
This paper introduces an innovative approach for image matting that redefines the traditional regression-based task as a generative modeling challenge.
DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration Models
This paper introduces a method for zero-shot video restoration using pre-trained image restoration diffusion models.
Going Beyond Word Matching: Syntax Improves In-context Example Selection for Machine Translation
In-context learning (ICL) is the trending prompting strategy in the era of large language models (LLMs), where a few examples are demonstrated to evoke LLMs' power for a given task.
Contributing Dimension Structure of Deep Feature for Coreset Selection
Existing methods typically measure both the representation and diversity of data based on similarity metrics, such as L2-norm.
HumanNeRF-SE: A Simple yet Effective Approach to Animate HumanNeRF with Diverse Poses
Our architecture involving both explicit and implicit representation is simple yet effective.
Moiré Backdoor Attack (MBA): A Novel Trigger for Pedestrian Detectors in the Physical World
Next, we embed these Moiré patterns as a backdoor trigger into digital images and use this dataset to train a backdoored detector.
Multi-level feature fusion network combining attention mechanisms for polyp segmentation
Firstly, features extracted by encoders are not adequately filtered and utilized.
Beyond Domain Gap: Exploiting Subjectivity in Sketch-Based Person Retrieval
2) Multi-perspective and multi-style.
DisCO: Portrait Distortion Correction with Perspective-Aware 3D GANs
Close-up facial images captured at short distances often suffer from perspective distortion, resulting in exaggerated facial features and unnatural/unattractive appearances.
Rethinking Video Frame Interpolation from Shutter Mode Induced Degradation
Image restoration from various motion-related degradations, like blurry effects recorded by a global shutter (GS) and jello effects caused by a rolling shutter (RS), has been extensively studied.
Single Image Deblurring with Row-dependent Blur Magnitude
Image degradation often occurs during fast camera or object movements, regardless of the exposure modes: global shutter (GS) or rolling shutter (RS).
HOTCOLD Block: Fooling Thermal Infrared Detectors with a Novel Wearable Design
Adversarial attacks on thermal infrared imaging expose the risk of related applications.
A Survey of Dataset Refinement for Problems in Computer Vision Datasets
In addition, we organize these dataset refinement methods according to the addressed data problems and provide a systematic comparative description.
Physical Adversarial Attack meets Computer Vision: A Decade Survey
Building upon this foundation, we uncover the pervasive role of artifacts carrying adversarial perturbations in the physical world.
Neural Global Shutter: Learn to Restore Video from a Rolling Shutter Camera with Global Reset Feature
In this paper, we investigate using rolling shutter with a global reset feature (RSGR) to restore clean global shutter (GS) videos.
Both Style and Fog Matter: Cumulative Domain Adaptation for Semantic Foggy Scene Understanding
Unlike previous methods that mainly focus on closing the domain gap caused by fog -- defogging the foggy images or fogging the clear images, we propose to alleviate the domain gap by considering fog influence and style variation simultaneously.
Ranked #4 on
Domain Adaptation
on Cityscapes-to-FoggyZurich
Domain-Specific Mappings for Generative Adversarial Style Transfer
For addressing this issue, this paper leverages domain-specific mappings for remapping latent features in the shared content space to domain-specific content spaces.
Learning to Reduce Dual-Level Discrepancy for Infrared-Visible Person Re-Identification
It is however difficult to eliminate the mixed discrepancies using only feature-level constraints.
Polarimetric Camera Calibration Using an LCD Monitor
It is crucial for polarimetric imaging to accurately calibrate the polarizer angles and the camera response function (CRF) of a polarizing camera.
Beyond Intra-modality: A Survey of Heterogeneous Person Re-identification
An efficient and effective person re-identification (ReID) system relieves the users from painful and boring video watching and accelerates the process of video analysis.
Illumination-Adaptive Person Re-identification
To demonstrate the illumination issue and to evaluate our model, we construct two large-scale simulated datasets with a wide range of illumination variations.
