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Found 14 papers, 7 papers with code
Real-World Computational Aberration Correction via Quantized Domain-Mixing Representation
Relying on paired synthetic data, existing learning-based Computational Aberration Correction (CAC) methods are confronted with the intricate and multifaceted synthetic-to-real domain gap, which leads to suboptimal performance in real-world applications.
FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous Driving
Based on the modeling method, we present FocusFlow, a framework consisting of 1) a mix loss function combined with a classic photometric loss function and our proposed Conditional Point Control Loss (CPCL) function for diverse point-wise supervision; 2) a conditioned controlling model which substitutes the conventional feature encoder by our proposed Condition Control Encoder (CCE).
See More and Know More: Zero-shot Point Cloud Segmentation via Multi-modal Visual Data
They typically align visual features with semantic features obtained from word embedding by the supervision of seen classes' annotations.
Semi-supervised multi-view concept decomposition
Concept Factorization (CF), as a novel paradigm of representation learning, has demonstrated superior performance in multi-view clustering tasks.
Minimalist and High-Quality Panoramic Imaging with PSF-aware Transformers
In this paper, we propose a Panoramic Computational Imaging Engine (PCIE) to address minimalist and high-quality panoramic imaging.
Event-Based Frame Interpolation with Ad-hoc Deblurring
The performance of video frame interpolation is inherently correlated with the ability to handle motion in the input scene.
SemanticBEVFusion: Rethink LiDAR-Camera Fusion in Unified Bird's-Eye View Representation for 3D Object Detection
LiDAR and camera are two essential sensors for 3D object detection in autonomous driving.
Beyond the Field-of-View: Enhancing Scene Visibility and Perception with Clip-Recurrent Transformer
In this paper, we propose the concept of online video inpainting for autonomous vehicles to expand the field of view, thereby enhancing scene visibility, perception, and system safety.
Ranked #1 on
Seeing Beyond the Visible
on KITTI360-EX
Computational Imaging for Machine Perception: Transferring Semantic Segmentation beyond Aberrations
Further, we propose Computational Imaging Assisted Domain Adaptation (CIADA) to leverage prior knowledge of CI for robust performance in SSOA.
Bear the Query in Mind: Visual Grounding with Query-conditioned Convolution
With our proposed QCM, the downstream fusion module receives visual features that are more discriminative and focused on the desired object described in the expression, leading to more accurate predictions.
Annular Computational Imaging: Capture Clear Panoramic Images through Simple Lens
In this paper, we propose an Annular Computational Imaging (ACI) framework to break the optical limit of light-weight PAL design.
DGSVis: Visual Analysis of Hierarchical Snapshots in Dynamic Graph
To provide an effective analysis method for this type of dynamic graph data, we propose a snapshot generation algorithm involving Human-In-Loop to help users divide the dynamic graphs into multi-granularity and hierarchical snapshots for further analysis.
Event-Based Fusion for Motion Deblurring with Cross-modal Attention
Traditional frame-based cameras inevitably suffer from motion blur due to long exposure times.
Ranked #3 on
Deblurring
on GoPro
(using extra training data)
Infrared Image Super-Resolution via Heterogeneous Convolutional WGAN
Recently, deep learning methods have dominated image super-resolution and achieved remarkable performance on visible images; however, IR images have received less attention.
