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Found 22 papers, 11 papers with code
DexGrasp Anything: Towards Universal Robotic Dexterous Grasping with Physics Awareness
A dexterous hand capable of grasping any object is essential for the development of general-purpose embodied intelligent robots.
Benchmarking the Robustness of Optical Flow Estimation to Corruptions
Optical flow estimation is extensively used in autonomous driving and video editing.
EI-Nexus: Towards Unmediated and Flexible Inter-Modality Local Feature Extraction and Matching for Event-Image Data
Event cameras, with high temporal resolution and high dynamic range, have limited research on the inter-modality local feature extraction and matching of event-image data.
EEPNet: Efficient Edge Pixel-based Matching Network for Cross-Modal Dynamic Registration between LiDAR and Camera
To address these issues, we propose EEPNet, an advanced network that leverages reflectance maps obtained from point cloud projections to enhance registration accuracy.
Towards Single-Lens Controllable Depth-of-Field Imaging via Depth-Aware Point Spread Functions
A Depth-aware Controllable DoF Imaging (DCDI) framework is proposed equipped with All-in-Focus (AiF) aberration correction and monocular depth estimation, where the recovered image and corresponding depth map are utilized to produce imaging results under diverse DoFs of any high-end lens via patch-wise convolution.
A Flexible Framework for Universal Computational Aberration Correction via Automatic Lens Library Generation and Domain Adaptation
OmniLens extends the idea of universal CAC to a broader concept, where a base model is trained for three cases, including zero-shot CAC with the pre-trained model, few-shot CAC with a little lens-specific data for fine-tuning, and domain adaptive CAC using domain adaptation for lens-descriptions-unknown lens.
Design, analysis, and manufacturing of a glass-plastic hybrid minimalist aspheric panoramic annular lens
We propose a high-performance glass-plastic hybrid minimalist aspheric panoramic annular lens (ASPAL) to solve several major limitations of the traditional panoramic annular lens (PAL), such as large size, high weight, and complex system.
Exploring Quasi-Global Solutions to Compound Lens Based Computational Imaging Systems
Recently, joint design approaches that simultaneously optimize optical systems and downstream algorithms through data-driven learning have demonstrated superior performance over traditional separate design approaches.
Representing Domain-Mixing Optical Degradation for Real-World Computational Aberration Correction via Vector Quantization
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 achieve 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.
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.
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
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 #2 on
Object Detection
on DSEC
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.
