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05/09/2023
Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation
Weakly Supervised Semantic Segmentation (WSSS) with only image-level sup...
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12/08/2022
LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models
This study focuses on embodied agents that can follow natural language i...
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09/12/2022
PreSTU: Pre-Training for Scene-Text Understanding
The ability to read and reason about texts in an image is often lacking ...
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09/24/2021
Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans
Accurately segmenting teeth and identifying the corresponding anatomical...
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06/30/2021
How to Train Your MAML to Excel in Few-Shot Classification
Model-agnostic meta-learning (MAML) is arguably the most popular meta-le...
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02/17/2021
A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection
Object frequencies in daily scenes follow a long-tailed distribution. Ma...
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09/04/2020
FedDistill: Making Bayesian Model Ensemble Applicable to Federated Learning
Federated learning aims to leverage users' own data and computational re...
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07/24/2020
MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation
Semi-supervised domain adaptation (SSDA) aims to adapt models from a lab...
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01/06/2020
Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning
We investigate learning a ConvNet classifier with class-imbalanced data....
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11/12/2019
SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning
Few-shot learners aim to recognize new object classes based on a small n...
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12/18/2018
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving
3D object detection is an essential task in autonomous driving. Recent t...
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05/26/2016
