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Found 43 papers, 13 papers with code
Large-Scale Gaussian Splatting SLAM
In tracking, we introduce feature-alignment warping constraints to alleviate the adverse effects of appearance similarity in rendering losses.
ElectricSight: 3D Hazard Monitoring for Power Lines Using Low-Cost Sensors
To address this challenge, we present ElectricSight, a system designed for 3D distance measurement and monitoring of potential hazards to power transmission lines.
A Framework for Benchmarking and Aligning Task-Planning Safety in LLM-Based Embodied Agents
Large Language Models (LLMs) exhibit substantial promise in enhancing task-planning capabilities within embodied agents due to their advanced reasoning and comprehension.
Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving
The significant achievements of pre-trained models leveraging large volumes of data in the field of NLP and 2D vision inspire us to explore the potential of extensive data pre-training for 3D perception in autonomous driving.
CAFE-AD: Cross-Scenario Adaptive Feature Enhancement for Trajectory Planning in Autonomous Driving
However, open-loop training on the nuPlan dataset tends to cause causal confusion during closed-loop testing, and the dataset also presents a long-tail distribution of scenarios.
GraspCoT: Integrating Physical Property Reasoning for 6-DoF Grasping under Flexible Language Instructions
In this work, we propose GraspCoT, a 6-DoF grasp detection framework that integrates a Chain-of-Thought (CoT) reasoning mechanism oriented to physical properties, guided by auxiliary question-answering (QA) tasks.
OG-Gaussian: Occupancy Based Street Gaussians for Autonomous Driving
Accurate and realistic 3D scene reconstruction enables the lifelike creation of autonomous driving simulation environments.
RaCFormer: Towards High-Quality 3D Object Detection via Query-based Radar-Camera Fusion
For the latter, we initially incorporate a radar-guided depth head to refine the transformation from image view to BEV.
Map++: Towards User-Participatory Visual SLAM Systems with Efficient Map Expansion and Sharing
We realized this approach by developing Map++, an efficient system that functions as a plug-and-play extension, supporting participatory map-building based on existing SLAM algorithms.
Harnessing Your DRAM and SSD for Sustainable and Accessible LLM Inference with Mixed-Precision and Multi-level Caching
To enhance communication efficiency, M2Cache maintains a neuron-level mixed-precision LRU cache in HBM, a larger layer-aware cache in DRAM, and a full model in SSD.
LFP: Efficient and Accurate End-to-End Lane-Level Planning via Camera-LiDAR Fusion
For performance, the lane-level cross-modal query integration and feature enhancement module uses confidence score from ROI to combine low-confidence image queries with LiDAR queries, extracting complementary depth features.
OccMamba: Semantic Occupancy Prediction with State Space Models
Inspired by the global modeling and linear computation complexity of the Mamba architecture, we present the first Mamba-based network for semantic occupancy prediction, termed OccMamba.
AutoRG-Brain: Grounded Report Generation for Brain MRI
To address these challenges, we initiate a series of work on grounded Automatic Report Generation (AutoRG), starting from the brain MRI interpretation system, which supports the delineation of brain structures, the localization of anomalies, and the generation of well-organized findings.
RayFormer: Improving Query-Based Multi-Camera 3D Object Detection via Ray-Centric Strategies
To extract unique object-level features that cater to distinct queries, we design a ray sampling method that suitably organizes the distribution of feature sampling points on both images and bird's eye view.
Perception Helps Planning: Facilitating Multi-Stage Lane-Level Integration via Double-Edge Structures
In this work, we endeavor to integrate the perception of these elements into the planning task.
LDP: A Local Diffusion Planner for Efficient Robot Navigation and Collision Avoidance
The complex conditional distribution in local navigation needs training data to include diverse policy in diverse real-world scenarios; (2) Myopic Observation.
The USTC-NERCSLIP Systems for The ICMC-ASR Challenge
This report describes the submitted system to the In-Car Multi-Channel Automatic Speech Recognition (ICMC-ASR) challenge, which considers the ASR task with multi-speaker overlapping and Mandarin accent dynamics in the ICMC case.
T-MAC: CPU Renaissance via Table Lookup for Low-Bit LLM Deployment on Edge
Weight quantization is crucial for reducing the memory footprint of LLMs on devices.
CLMASP: Coupling Large Language Models with Answer Set Programming for Robotic Task Planning
This plan is then refined by an ASP program with a robot's action knowledge, which integrates implementation details into the skeleton, grounding the LLM's abstract outputs in practical robot contexts.
MM-Gaussian: 3D Gaussian-based Multi-modal Fusion for Localization and Reconstruction in Unbounded Scenes
In this work, we present MM-Gaussian, a LiDAR-camera multi-modal fusion system for localization and mapping in unbounded scenes.
CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks
Numerous roadside perception datasets have been introduced to propel advancements in autonomous driving and intelligent transportation systems research and development.
HVDistill: Transferring Knowledge from Images to Point Clouds via Unsupervised Hybrid-View Distillation
We present a hybrid-view-based knowledge distillation framework, termed HVDistill, to guide the feature learning of a point cloud neural network with a pre-trained image network in an unsupervised man- ner.
Agent3D-Zero: An Agent for Zero-shot 3D Understanding
The ability to understand and reason the 3D real world is a crucial milestone towards artificial general intelligence.
PoIFusion: Multi-Modal 3D Object Detection via Fusion at Points of Interest
In particular, our PoIFusion follows the paradigm of query-based object detection, formulating object queries as dynamic 3D boxes and generating a set of PoIs based on each query box.
DGR: A General Graph Desmoothing Framework for Recommendation via Global and Local Perspectives
Graph Convolutional Networks (GCNs) have become pivotal in recommendation systems for learning user and item embeddings by leveraging the user-item interaction graph's node information and topology.
CalibFormer: A Transformer-based Automatic LiDAR-Camera Calibration Network
The fusion of LiDARs and cameras has been increasingly adopted in autonomous driving for perception tasks.
EdgeCalib: Multi-Frame Weighted Edge Features for Automatic Targetless LiDAR-Camera Calibration
The edge features, which are prevalent in various environments, are aligned in both images and point clouds to determine the extrinsic parameters.
UniBrain: Universal Brain MRI Diagnosis with Hierarchical Knowledge-enhanced Pre-training
Magnetic resonance imaging~(MRI) have played a crucial role in brain disease diagnosis, with which a range of computer-aided artificial intelligence methods have been proposed.
Bi-LRFusion: Bi-Directional LiDAR-Radar Fusion for 3D Dynamic Object Detection
LiDAR and Radar are two complementary sensing approaches in that LiDAR specializes in capturing an object's 3D shape while Radar provides longer detection ranges as well as velocity hints.
USTC FLICAR: A Sensors Fusion Dataset of LiDAR-Inertial-Camera for Heavy-duty Autonomous Aerial Work Robots
In this paper, we present the USTC FLICAR Dataset, which is dedicated to the development of simultaneous localization and mapping and precise 3D reconstruction of the workspace for heavy-duty autonomous aerial work robots.
$P^{3}O$: Transferring Visual Representations for Reinforcement Learning via Prompting
In particular, we specify a prompt-transformer for representation conversion and propose a two-step training process to train the prompt-transformer for the target environment, while the rest of the DRL pipeline remains unchanged.
Deep Reinforcement Learning for Localizability-Enhanced Navigation in Dynamic Human Environments
The planner learns to assign different importance to the geometric features and encourages the robot to navigate through areas that are helpful for laser localization.
TrajMatch: Towards Automatic Spatio-temporal Calibration for Roadside LiDARs through Trajectory Matching
In this paper, we propose TrajMatch -- the first system that can automatically calibrate for roadside LiDARs in both time and space.
OA-BEV: Bringing Object Awareness to Bird's-Eye-View Representation for Multi-Camera 3D Object Detection
To this end, we propose OA-BEV, a network that can be plugged into the BEV-based 3D object detection framework to bring out the objects by incorporating object-aware pseudo-3D features and depth features.
TLP: A Deep Learning-based Cost Model for Tensor Program Tuning
Instead of extracting features from the tensor program itself, TLP extracts features from the schedule primitives.
TransVG++: End-to-End Visual Grounding with Language Conditioned Vision Transformer
For another, we devise Language Conditioned Vision Transformer that removes external fusion modules and reuses the uni-modal ViT for vision-language fusion at the intermediate layers.
VPFNet: Improving 3D Object Detection with Virtual Point based LiDAR and Stereo Data Fusion
However, this approach often suffers from the mismatch between the resolution of point clouds and RGB images, leading to sub-optimal performance.
Reinforcement Learning for Robot Navigation with Adaptive Forward Simulation Time (AFST) in a Semi-Markov Model
Deep reinforcement learning (DRL) algorithms have proven effective in robot navigation, especially in unknown environments, by directly mapping perception inputs into robot control commands.
From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object Detection
To this end, in this work, we regard point clouds as hollow-3D data and propose a new architecture, namely Hallucinated Hollow-3D R-CNN ($\text{H}^2$3D R-CNN), to address the problem of 3D object detection.
Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance Voting
As cameras are increasingly deployed in new application domains such as autonomous driving, performing 3D object detection on monocular images becomes an important task for visual scene understanding.
Multi-Modal 3D Object Detection in Autonomous Driving: a Survey
In this survey, we first introduce the background of popular sensors used for self-driving, their data properties, and the corresponding object detection algorithms.
Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection
In this paper, we take a slightly different viewpoint -- we find that precise positioning of raw points is not essential for high performance 3D object detection and that the coarse voxel granularity can also offer sufficient detection accuracy.
Ranked #4 on
3D Object Detection
on KITTI Cars Moderate val
Two-dimensional Anti-jamming Mobile Communication Based on Reinforcement Learning
It is shown that, by applying reinforcement learning techniques, a mobile device can achieve an optimal communication policy without the need to know the jamming and interference model and the radio channel model in a dynamic game framework.
