Search Results for author:
Found 16 papers, 9 papers with code
BiSeg-SAM: Weakly-Supervised Post-Processing Framework for Boosting Binary Segmentation in Segment Anything Models
While various segmentation methods for polyps and skin lesions using fully supervised deep learning techniques have been developed, the pixel-level annotation of medical images by doctors is both time-consuming and costly.
CoDa-4DGS: Dynamic Gaussian Splatting with Context and Deformation Awareness for Autonomous Driving
By aggregating and encoding both semantic and temporal deformation features, each Gaussian is equipped with cues for potential deformation compensation within 3D space, facilitating a more precise representation of dynamic scenes.
TUMTraffic-VideoQA: A Benchmark for Unified Spatio-Temporal Video Understanding in Traffic Scenes
We present TUMTraffic-VideoQA, a novel dataset and benchmark designed for spatio-temporal video understanding in complex roadside traffic scenarios.
UniLoc: Towards Universal Place Recognition Using Any Single Modality
To date, most place recognition methods focus on single-modality retrieval.
Dataset Distillation by Automatic Training Trajectories
Dataset Distillation is used to create a concise, yet informative, synthetic dataset that can replace the original dataset for training purposes.
Embracing Events and Frames with Hierarchical Feature Refinement Network for Object Detection
The core concept is the design of the coarse-to-fine fusion module, denoted as the cross-modality adaptive feature refinement (CAFR) module.
Ranked #1 on
Object Detection
on PKU-DDD17-Car
Collaborative Semantic Occupancy Prediction with Hybrid Feature Fusion in Connected Automated Vehicles
Additionally, due to the lack of a collaborative perception dataset designed for semantic occupancy prediction, we augment a current collaborative perception dataset to include 3D collaborative semantic occupancy labels for a more robust evaluation.
Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning
Moreover, we confirm this observation for object detection on a novel synthetic-to-real benchmark.
Ranked #1 on
Semantic Segmentation
on BDD100K val
Transformation Decoupling Strategy based on Screw Theory for Deterministic Point Cloud Registration with Gravity Prior
This paper focuses on addressing the robust correspondence-based registration problem with gravity prior that often arises in practice.
Vision Language Models in Autonomous Driving: A Survey and Outlook
The applications of Vision-Language Models (VLMs) in the field of Autonomous Driving (AD) have attracted widespread attention due to their outstanding performance and the ability to leverage Large Language Models (LLMs).
Efficient and Deterministic Search Strategy Based on Residual Projections for Point Cloud Registration with Correspondences
Moreover, our method can be adapted to address the challenging problem of simultaneous pose and registration.
Spatio-temporal Tendency Reasoning for Human Body Pose and Shape Estimation from Videos
Different from them, our STR aims to learn accurate and natural motion sequences in an unconstrained environment through temporal and spatial tendency and to fully excavate the spatio-temporal features of existing video data.
Ranked #61 on
3D Human Pose Estimation
on MPI-INF-3DHP
OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction
Event extraction (EE) is an essential task of information extraction, which aims to extract structured event information from unstructured text.
Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation
In the past few years, convolutional neural networks (CNNs) have achieved milestones in medical image analysis.
Ranked #5 on
Medical Image Segmentation
on ACDC
Lightweight Convolutional Neural Network with Gaussian-based Grasping Representation for Robotic Grasping Detection
Extensive experiments on two public grasping datasets, Cornell and Jacquard demonstrate the state-of-the-art performance of our method in balancing accuracy and inference speed.
Ranked #1 on
Robotic Grasping
on Jacquard dataset
Event-based Robotic Grasping Detection with Neuromorphic Vision Sensor and Event-Stream Dataset
Based on the Event-Stream dataset, we develop a deep neural network for grasping detection which consider the angle learning problem as classification instead of regression.
