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09/20/2023
StructChart: Perception, Structuring, Reasoning for Visual Chart Understanding
Charts are common in literature across different scientific fields, conv...
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09/19/2023
SPOT: Scalable 3D Pre-training via Occupancy Prediction for Autonomous Driving
Annotating 3D LiDAR point clouds for perception tasks including 3D objec...
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09/11/2023
ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation
Domain shifts such as sensor type changes and geographical situation var...
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08/01/2023
DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving
End-to-end autonomous driving aims to build a fully differentiable syste...
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06/23/2023
Patch-Level Contrasting without Patch Correspondence for Accurate and Dense Contrastive Representation Learning
We propose ADCLR: A ccurate and D ense Contrastive Representation Learni...
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06/20/2023
GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks
Graph structure learning is a well-established problem that aims at opti...
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06/14/2023
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification
Graph neural networks have been extensively studied for learning with in...
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05/10/2023
Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving
End-to-end autonomous driving has made impressive progress in recent yea...
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05/07/2023
HIORE: Leveraging High-order Interactions for Unified Entity Relation Extraction
Entity relation extraction consists of two sub-tasks: entity recognition...
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04/10/2023
H2RBox-v2: Boosting HBox-supervised Oriented Object Detection via Symmetric Learning
With the increasing demand for oriented object detection e.g. in autonom...
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04/06/2023
Geometric-aware Pretraining for Vision-centric 3D Object Detection
Multi-camera 3D object detection for autonomous driving is a challenging...
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03/25/2023
Active Finetuning: Exploiting Annotation Budget in the Pretraining-Finetuning Paradigm
Given the large-scale data and the high annotation cost, pretraining-fin...
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03/22/2023
EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning
Dynamic graphs arise in various real-world applications, and it is often...
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03/09/2023
R-Tuning: Regularized Prompt Tuning in Open-Set Scenarios
In realistic open-set scenarios where labels of a part of testing data a...
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03/09/2023
Rethinking Visual Prompt Learning as Masked Visual Token Modeling
Prompt learning has achieved great success in efficiently exploiting lar...
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03/09/2023
ARS-DETR: Aspect Ratio Sensitive Oriented Object Detection with Transformer
Existing oriented object detection methods commonly use metric AP_50 to ...
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02/08/2023
Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution
Inductive one-bit matrix completion is motivated by modern applications ...
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02/06/2023
Energy-based Out-of-Distribution Detection for Graph Neural Networks
Learning on graphs, where instance nodes are inter-connected, has become...
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01/23/2023
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion
Real-world data generation often involves complex inter-dependencies amo...
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01/03/2023
Policy Pre-training for End-to-end Autonomous Driving via Self-supervised Geometric Modeling
Witnessing the impressive achievements of pre-training techniques on lar...
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12/18/2022
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs
Graph neural networks (GNNs), as the de-facto model class for representa...
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12/03/2022
Leveraging Angular Information Between Feature and Classifier for Long-tailed Learning: A Prediction Reformulation Approach
Deep neural networks still struggle on long-tailed image datasets, and o...
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10/24/2022
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks
We study a new paradigm of knowledge transfer that aims at encoding grap...
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10/24/2022
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment
The goal of sequential event prediction is to estimate the next event ba...
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10/19/2022
Learning Universe Model for Partial Matching Networks over Multiple Graphs
We consider the general setting for partial matching of two or multiple ...
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10/13/2022
H2RBox: Horizonal Box Annotation is All You Need for Oriented Object Detection
Oriented object detection emerges in many applications from aerial image...
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09/22/2022
Detecting Rotated Objects as Gaussian Distributions and Its 3-D Generalization
Existing detection methods commonly use a parameterized bounding box (BB...
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07/15/2022
ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learning
Many existing autonomous driving paradigms involve a multi-stage discret...
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06/16/2022
Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline
Current end-to-end autonomous driving methods either run a controller ba...
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06/02/2022
Learning Unbiased Transferability for Domain Adaptation by Uncertainty Modeling
Domain adaptation (DA) aims to transfer knowledge learned from a labeled...
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05/26/2022
On Collective Robustness of Bagging Against Data Poisoning
Bootstrap aggregating (bagging) is an effective ensemble protocol, which...
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05/21/2022
CEP3: Community Event Prediction with Neural Point Process on Graph
Many real world applications can be formulated as event forecasting on C...
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04/30/2022
HDGT: Heterogeneous Driving Graph Transformer for Multi-Agent Trajectory Prediction via Scene Encoding
One essential task for autonomous driving is to encode the information o...
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04/28/2022
DOTIN: Dropping Task-Irrelevant Nodes for GNNs
Scalability is an important consideration for deep graph neural networks...
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04/28/2022
MMRotate: A Rotated Object Detection Benchmark using Pytorch
We present an open-source toolbox, named MMRotate, which provides a cohe...
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04/18/2022
MHSCNet: A Multimodal Hierarchical Shot-aware Convolutional Network for Video Summarization
Video summarization intends to produce a concise video summary by effect...
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04/02/2022
Modeling Dynamic User Preference via Dictionary Learning for Sequential Recommendation
Capturing the dynamics in user preference is crucial to better predict u...
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03/30/2022
Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation
User interests are usually dynamic in the real world, which poses both t...
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03/24/2022
GraphCoCo: Graph Complementary Contrastive Learning
Graph Contrastive Learning (GCL) has shown promising performance in grap...
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03/21/2022
EAutoDet: Efficient Architecture Search for Object Detection
Training CNN for detection is time-consuming due to the large dataset an...
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03/17/2022
Object Localization under Single Coarse Point Supervision
Point-based object localization (POL), which pursues high-performance ob...
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03/15/2022
DialogueNeRF: Towards Realistic Avatar Face-to-face Conversation Video Generation
Conversation is an essential component of virtual avatar activities in t...
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03/06/2022
A Survey for Solving Mixed Integer Programming via Machine Learning
This paper surveys the trend of leveraging machine learning to solve mix...
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03/02/2022
Machine Learning Methods in Solving the Boolean Satisfiability Problem
This paper reviews the recent literature on solving the Boolean satisfia...
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02/28/2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview
The past few years have witnessed an increased interest in learning Hami...
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02/28/2022
Towards Machine Learning for Placement and Routing in Chip Design: a Methodological Overview
Placement and routing are two indispensable and challenging (NP-hard) ta...
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02/15/2022
Transformers in Time Series: A Survey
Transformers have achieved superior performances in many tasks in natura...
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02/01/2022
GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks
Recovering global rankings from pairwise comparisons is an important pro...
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01/29/2022
The KFIoU Loss for Rotated Object Detection
Differing from the well-developed horizontal object detection area where...
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01/13/2022