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Found 35 papers, 15 papers with code
Scaling Multi-Camera 3D Object Detection through Weak-to-Strong Eliciting
Finally, for MC3D-Det joint training, the elaborate dataset merge strategy is designed to solve the problem of inconsistent camera numbers and camera parameters.
Spurious Correlations in Machine Learning: A Survey
Machine learning systems are known to be sensitive to spurious correlations between biased features of the inputs (e. g., background, texture, and secondary objects) and the corresponding labels.
Exploring the Impact of In-Browser Deep Learning Inference on Quality of User Experience and Performance
Additionally, we noticed that in-browser inference increases the time it takes for graphical user interface (GUI) components to load in web browsers by a significant 67. 2\%, which severely impacts the overall QoE for users of web applications that depend on this technology.
If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents
The prominent large language models (LLMs) of today differ from past language models not only in size, but also in the fact that they are trained on a combination of natural language and formal language (code).
SuperNormal: Neural Surface Reconstruction via Multi-View Normal Integration
We present SuperNormal, a fast, high-fidelity approach to multi-view 3D reconstruction using surface normal maps.
LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs
Autonomous driving (AD) has made significant strides in recent years.
A Survey on Multimodal Large Language Models for Autonomous Driving
We first introduce the background of Multimodal Large Language Models (MLLMs), the multimodal models development using LLMs, and the history of autonomous driving.
MACP: Efficient Model Adaptation for Cooperative Perception
We approach this objective by identifying the key challenges of shifting from single-agent to cooperative settings, adapting the model by freezing most of its parameters and adding a few lightweight modules.
Receive, Reason, and React: Drive as You Say with Large Language Models in Autonomous Vehicles
The fusion of human-centric design and artificial intelligence (AI) capabilities has opened up new possibilities for next-generation autonomous vehicles that go beyond transportation.
PIE: Simulating Disease Progression via Progressive Image Editing
Disease progression simulation is a crucial area of research that has significant implications for clinical diagnosis, prognosis, and treatment.
Drive as You Speak: Enabling Human-Like Interaction with Large Language Models in Autonomous Vehicles
The future of autonomous vehicles lies in the convergence of human-centric design and advanced AI capabilities.
Accelerating In-Browser Deep Learning Inference on Diverse Edge Clients through Just-in-Time Kernel Optimizations
Web applications are increasingly becoming the primary platform for AI service delivery, making in-browser deep learning (DL) inference more prominent.
Mitigating Transformer Overconfidence via Lipschitz Regularization
Though Transformers have achieved promising results in many computer vision tasks, they tend to be over-confident in predictions, as the standard Dot Product Self-Attention (DPSA) can barely preserve distance for the unbounded input domain.
Learning Remote Sensing Object Detection with Single Point Supervision
In this paper, we make the first attempt to achieve RS object detection with single point supervision, and propose a PSOD method tailored for RS images.
CEMFormer: Learning to Predict Driver Intentions from In-Cabin and External Cameras via Spatial-Temporal Transformers
Driver intention prediction seeks to anticipate drivers' actions by analyzing their behaviors with respect to surrounding traffic environments.
Multi-View Azimuth Stereo via Tangent Space Consistency
We present a method for 3D reconstruction only using calibrated multi-view surface azimuth maps.
SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction
SuperScaler is a system that facilitates the design and generation of highly flexible parallelization plans.
THMA: Tencent HD Map AI System for Creating HD Map Annotations
THMA has been deployed by the Tencent Map team to provide services to downstream companies and users, serving over 1, 000 labeling workers and producing more than 30, 000 kilometers of HD map data per day at most.
ECON: Explicit Clothed humans Optimized via Normal integration
To increase robustness for these cases, existing work uses an explicit parametric body model to constrain surface reconstruction, but this limits the recovery of free-form surfaces such as loose clothing that deviates from the body.
ViTASD: Robust Vision Transformer Baselines for Autism Spectrum Disorder Facial Diagnosis
Research progress in the field of ASD facial analysis in pediatric patients has been hindered due to a lack of well-established baselines.
Automatic Infectious Disease Classification Analysis with Concept Discovery
Automatic infectious disease classification from images can facilitate needed medical diagnoses.
A Compacted Structure for Cross-domain learning on Monocular Depth and Flow Estimation
A dual-head mechanism is used to predict optical flow for rigid and non-rigid motion based on a divide-and-conquer manner, which significantly improves the optical flow estimation performance.
Improving Computed Tomography (CT) Reconstruction via 3D Shape Induction
Chest computed tomography (CT) imaging adds valuable insight in the diagnosis and management of pulmonary infectious diseases, like tuberculosis (TB).
AggPose: Deep Aggregation Vision Transformer for Infant Pose Estimation
We show that AggPose outperforms hybrid model HRFormer and TokenPose in the infant pose estimation dataset.
Ranked #7 on
Keypoint Detection
on MS COCO
Normal Integration via Inverse Plane Fitting With Minimum Point-to-Plane Distance
Experimental results on analytically computed, synthetic, and real-world surfaces show that our method yields accurate and stable reconstruction for both orthographic and perspective normal maps.
VeniBot: Towards Autonomous Venipuncture with Semi-supervised Vein Segmentation from Ultrasound Images
In the modern medical care, venipuncture is an indispensable procedure for both diagnosis and treatment.
VeniBot: Towards Autonomous Venipuncture with Automatic Puncture Area and Angle Regression from NIR Images
For the automation, we focus on the positioning part and propose a Dual-In-Dual-Out network based on two-step learning and two-task learning, which can achieve fully automatic regression of the suitable puncture area and angle from near-infrared(NIR) images.
Treatment Planning System for Electron FLASH Radiotherapy: Open-source for Clinical Implementation
eFLASH-RT plans were MC forward calculated in Geant4 for a mouse brain treatment and compared to a conventional (Conv-RT) plan in Eclipse for a human patient with metastatic renal cell carcinoma.
Medical Physics
Balanced Joint Adversarial Training for Robust Intent Detection and Slot Filling
Joint intent detection and slot filling has recently achieved tremendous success in advancing the performance of utterance understanding.
Stereoscopic Flash and No-Flash Photography for Shape and Albedo Recovery
From the stereo image pair, we recover a rough shape that captures low-frequency shape variation without high-frequency details.
CAggNet: Crossing Aggregation Network for Medical Image Segmentation
In this paper, we present Crossing Aggregation Network (CAggNet), a novel densely connected semantic segmentation approach for medical image analysis.
UCT-ADP Progressive Bias Algorithm for Solving Gomoku
We combine Adaptive Dynamic Programming (ADP), a reinforcement learning method and UCB applied to trees (UCT) algorithm with a more powerful heuristic function based on Progressive Bias method and two pruning strategies for a traditional board game Gomoku.
Neural Style Transfer for Point Clouds
How can we edit or transform the geometric or color property of a point cloud?
Point Cloud Colorization Based on Densely Annotated 3D Shape Dataset
This paper introduces DensePoint, a densely sampled and annotated point cloud dataset containing over 10, 000 single objects across 16 categories, by merging different kind of information from two existing datasets.
L2GSCI: Local to Global Seam Cutting and Integrating for Accurate Face Contour Extraction
Current face alignment algorithms can robustly find a set of landmarks along face contour.
