Search Results for author:
Found 21 papers, 10 papers with code
Roadside Monocular 3D Detection via 2D Detection Prompting
Our method builds on a key insight that, compared with 3D detectors, a 2D detector is much easier to train and performs significantly better w. r. t detections on the 2D image plane.
3D-SceneDreamer: Text-Driven 3D-Consistent Scene Generation
Text-driven 3D scene generation techniques have made rapid progress in recent years.
Long-Tailed 3D Detection via 2D Late Fusion
Autonomous vehicles (AVs) must accurately detect objects from both common and rare classes for safe navigation, motivating the problem of Long-Tailed 3D Object Detection (LT3D).
Beyond Isolation: Multi-Agent Synergy for Improving Knowledge Graph Construction
Knowledge graph construction (KGC) is a multifaceted undertaking involving the extraction of entities, relations, and events.
Holistic Inverse Rendering of Complex Facade via Aerial 3D Scanning
In this work, we use multi-view aerial images to reconstruct the geometry, lighting, and material of facades using neural signed distance fields (SDFs).
M$^3$CS: Multi-Target Masked Point Modeling with Learnable Codebook and Siamese Decoders
Specifically, with masked point cloud as input, M$^3$CS introduces two decoders to predict masked representations and the original points simultaneously.
Cognitive Mirage: A Review of Hallucinations in Large Language Models
Our contribution are threefold: (1) We provide a detailed and complete taxonomy for hallucinations appearing in text generation tasks; (2) We provide theoretical analyses of hallucinations in LLMs and provide existing detection and improvement methods; (3) We propose several research directions that can be developed in the future.
ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich Document Images
It is hoped that this competition will attract many researchers in the field of CV and NLP, and bring some new thoughts to the field of Document AI.
SelFLoc: Selective Feature Fusion for Large-scale Point Cloud-based Place Recognition
To enhance message passing along particular axes, Stacked Asymmetric Convolution Block (SACB) is designed, which is one of the main contributions in this paper.
Visual Information Extraction in the Wild: Practical Dataset and End-to-end Solution
We evaluate the existing end-to-end methods for VIE on the proposed dataset and observe that the performance of these methods has a distinguishable drop from SROIE (a widely used English dataset) to our proposed dataset due to the larger variance of layout and entities.
SOOD: Towards Semi-Supervised Oriented Object Detection
Semi-Supervised Object Detection (SSOD), aiming to explore unlabeled data for boosting object detectors, has become an active task in recent years.
I$^2$-SDF: Intrinsic Indoor Scene Reconstruction and Editing via Raytracing in Neural SDFs
In this work, we present I$^2$-SDF, a new method for intrinsic indoor scene reconstruction and editing using differentiable Monte Carlo raytracing on neural signed distance fields (SDFs).
Turning a CLIP Model into a Scene Text Detector
Recently, pretraining approaches based on vision language models have made effective progresses in the field of text detection.
I2-SDF: Intrinsic Indoor Scene Reconstruction and Editing via Raytracing in Neural SDFs
Further, we propose to decompose the neural radiance field into spatially-varying material of the scene as a neural field through surface-based, differentiable Monte Carlo raytracing and emitter semantic segmentations, which enables physically based and photorealistic scene relighting and editing applications.
SASFormer: Transformers for Sparsely Annotated Semantic Segmentation
In this work, we propose a simple yet effective sparse annotated semantic segmentation framework based on segformer, dubbed SASFormer, that achieves remarkable performance.
PriorLane: A Prior Knowledge Enhanced Lane Detection Approach Based on Transformer
Lane detection is one of the fundamental modules in self-driving.
An Interactive Image-based Modeling System
This paper propose a interactive 3D modeling method and corresponding system based on single or multiple uncalibrated images.
AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification
The discovered attention cells can be seamlessly inserted into existing backbone networks, e. g., I3D or S3D, and improve video classification accuracy by more than 2% on both Kinetics-600 and MiT datasets.
MediaPipe: A Framework for Building Perception Pipelines
A developer can use MediaPipe to build prototypes by combining existing perception components, to advance them to polished cross-platform applications and measure system performance and resource consumption on target platforms.
Distributed, Parallel, and Cluster Computing
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
Therefore, we propose to search the network level structure in addition to the cell level structure, which forms a hierarchical architecture search space.
Ranked #7 on
Semantic Segmentation
on PASCAL VOC 2012 val
Progressive Neural Architecture Search
We propose a new method for learning the structure of convolutional neural networks (CNNs) that is more efficient than recent state-of-the-art methods based on reinforcement learning and evolutionary algorithms.
Ranked #15 on
Neural Architecture Search
on NAS-Bench-201, ImageNet-16-120
(Accuracy (Val) metric)
