Search Results for author:
Found 34 papers, 22 papers with code
MambaMOS: LiDAR-based 3D Moving Object Segmentation with Motion-aware State Space Model
In this paper, we propose a novel LiDAR-based 3D Moving Object Segmentation with Motion-aware State Space Model, termed MambaMOS.
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.
OccFiner: Offboard Occupancy Refinement with Hybrid Propagation
Vision-based occupancy prediction, also known as 3D Semantic Scene Completion (SSC), presents a significant challenge in computer vision.
Investigation of Adapter for Automatic Speech Recognition in Noisy Environment
Adapting an automatic speech recognition (ASR) system to unseen noise environments is crucial.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Towards Precise 3D Human Pose Estimation with Multi-Perspective Spatial-Temporal Relational Transformers
Due to the challenges in data collection, mainstream datasets of 3D human pose estimation are primarily composed of multi-view video data collected in laboratory environments, which contains rich spatial-temporal correlation information besides the image frame content.
Rethinking Event-based Human Pose Estimation with 3D Event Representations
Experiments on EV-3DPW demonstrate that the robustness of our proposed 3D representation methods compared to traditional RGB images and event frame techniques under the same backbones.
CoBEV: Elevating Roadside 3D Object Detection with Depth and Height Complementarity
Roadside camera-driven 3D object detection is a crucial task in intelligent transportation systems, which extends the perception range beyond the limitations of vision-centric vehicles and enhances road safety.
Ranked #2 on
3D Object Detection
on Rope3D
MS-Net: A Multi-modal Self-supervised Network for Fine-Grained Classification of Aircraft in SAR Images
However, it still has some drawbacks in SAR target classification, especially in fine-grained classification of aircraft: aircrafts in SAR images have large intra-class diversity and inter-class similarity; the number of effective samples is insufficient and it's hard to annotate.
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).
A Self-supervised SAR Image Despeckling Strategy Based on Parameter-sharing Convolutional Neural Networks
The training image pairs are generated by the sub-sampler from real-word SAR image to estimate the noise distribution.
Towards Anytime Optical Flow Estimation with Event Cameras
We then propose EVA-Flow, an EVent-based Anytime Flow estimation network to produce high-frame-rate event optical flow with only low-frame-rate optical flow ground truth for supervision.
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.
LF-PGVIO: A Visual-Inertial-Odometry Framework for Large Field-of-View Cameras using Points and Geodesic Segments
The purpose of our research is to unleash the potential of point-line odometry with large-FoV omnidirectional cameras, even for cameras with negative-plane FoV.
Diffusion-Based Speech Enhancement with Joint Generative and Predictive Decoders
At the decoded feature level, we fuse the two decoded features by generative and predictive decoders.
Bi-Mapper: Holistic BEV Semantic Mapping for Autonomous Driving
At the same time, an Across-Space Loss (ASL) is designed to mitigate the negative impact of geometric distortions.
FishDreamer: Towards Fisheye Semantic Completion via Unified Image Outpainting and Segmentation
This paper raises the new task of Fisheye Semantic Completion (FSC), where dense texture, structure, and semantics of a fisheye image are inferred even beyond the sensor field-of-view (FoV).
PanoVPR: Towards Unified Perspective-to-Equirectangular Visual Place Recognition via Sliding Windows across the Panoramic View
To address this, we propose \textit{PanoVPR}, a perspective-to-equirectangular (P2E) visual place recognition framework that employs sliding windows to eliminate feature truncation caused by hard cropping.
360BEV: Panoramic Semantic Mapping for Indoor Bird's-Eye View
Seeing only a tiny part of the whole is not knowing the full circumstance.
Delivering Arbitrary-Modal Semantic Segmentation
To make this possible, we present the arbitrary cross-modal segmentation model CMNeXt.
Ranked #1 on
Semantic Segmentation
on DSEC
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
Monolingual Recognizers Fusion for Code-switching Speech Recognition
It has two stages: the speech awareness (SA) stage and the language fusion (LF) stage.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
LF-VISLAM: A SLAM Framework for Large Field-of-View Cameras with Negative Imaging Plane on Mobile Agents
As loop closure on wide-FoV panoramic data further comes with a large number of outliers, traditional outlier rejection methods are not directly applicable.
Behind Every Domain There is a Shift: Adapting Distortion-aware Vision Transformers for Panoramic Semantic Segmentation
In this paper, we address panoramic semantic segmentation which is under-explored due to two critical challenges: (1) image distortions and object deformations on panoramas; (2) lack of semantic annotations in the 360-degree imagery.
Ranked #1 on
Semantic Segmentation
on SynPASS
Language-specific Characteristic Assistance for Code-switching Speech Recognition
Dual-encoder structure successfully utilizes two language-specific encoders (LSEs) for code-switching speech recognition.
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.
Efficient Human Pose Estimation via 3D Event Point Cloud
We then leverage the rasterized event point cloud as input to three different backbones, PointNet, DGCNN, and Point Transformer, with two linear layer decoders to predict the location of human keypoints.
Ranked #1 on
3D Human Pose Estimation
on DHP19
DCAN: Diversified News Recommendation with Coverage-Attentive Networks
Self-attention based models are widely used in news recommendation tasks.
Review on Panoramic Imaging and Its Applications in Scene Understanding
However, while satisfying the need for large-FoV photographic imaging, panoramic imaging instruments are expected to have high resolution, no blind area, miniaturization, and multidimensional intelligent perception, and can be combined with artificial intelligence methods towards the next generation of intelligent instruments, enabling deeper understanding and more holistic perception of 360-degree real-world surrounding environments.
An Improved Automatic Modulation Classification Scheme Based on Adaptive Fusion Network
Moreover, a novel confidence weighted loss function is proposed to address the imbalance issue and it is implemented by a two-stage learning scheme. Through the two-stage learning, AFNet can focus on high-confidence samples with more valid information and extract effective representations, so as to improve the overall classification performance.
PanoFlow: Learning 360° Optical Flow for Surrounding Temporal Understanding
PanoFlow achieves state-of-the-art performance on the public OmniFlowNet and the established FlowScape benchmarks.
LF-VIO: A Visual-Inertial-Odometry Framework for Large Field-of-View Cameras with Negative Plane
To tackle this issue, we propose LF-VIO, a real-time VIO framework for cameras with extremely large FoV.
CSFlow: Learning Optical Flow via Cross Strip Correlation for Autonomous Driving
In this paper, we propose a new deep network architecture for optical flow estimation in autonomous driving--CSFlow, which consists of two novel modules: Cross Strip Correlation module (CSC) and Correlation Regression Initialization module (CRI).
Feature-Area Optimization: A Novel SAR Image Registration Method
This letter proposes a synthetic aperture radar (SAR) image registration method named Feature-Area Optimization (FAO).
