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Chenqiang Gao

8 accepted papers

2026

MPL: Match-guided Prototype Learning for Few-shot Action Recognition

CVPR 2026

Current few-shot action recognition methods achieve impressive performance by learning representative prototypes and designing diverse video matching strategies. However, these approaches typically face two critical limitations: i) prototypes learned through implicit sample interactions lack clear s

Cited by 0SourcecodeScholar
2024

Learning Interaction-aware 3D Gaussian Splatting for One-shot Hand Avatars

NeurIPS 2024poster

In this paper, we propose to create animatable avatars for interacting hands with 3D Gaussian Splatting (GS) and single-image inputs. Existing GS-based methods designed for single subjects often yield unsatisfactory results due to limited input views, various hand poses, and occlusions. To address t…

2023

Hierarchical Supervision and Shuffle Data Augmentation for 3D Semi-Supervised Object Detection

CVPR 2023poster

State-of-the-art 3D object detectors are usually trained on large-scale datasets with high-quality 3D annotations. However, such 3D annotations are often expensive and time-consuming, which may not be practical for real applications. A natural remedy is to adopt semi-supervised learning (SSL) by lev…

2022

SS3D: Sparsely-Supervised 3D Object Detection From Point Cloud

CVPR 2022poster

Conventional deep learning based methods for 3D object detection require a large amount of 3D bounding box annotations for training, which is expensive to obtain in practice. Sparsely annotated object detection, which can largely reduce the annotations, is very challenging since the missingannotated…

Cited by 28PDFcodeScholar
2021

TSGCNet: Discriminative Geometric Feature Learning With Two-Stream Graph Convolutional Network for 3D Dental Model Segmentation

CVPR 2021poster

The ability to segment teeth precisely from digitized 3D dental models is an essential task in computer-aided orthodontic surgical planning. To date, deep learning based methods have been popularly used to handle this task. State-of-the-art methods directly concatenate the raw attributes of 3D input…

Cited by 55PDFcodeScholar
2019

Weakly Supervised Instance Segmentation Using Hybrid Networks

ICASSP 2019accepted

Weakly-supervised instance segmentation, which could greatly save labor and time cost of pixel mask annotation, has attracted increasing attention in recent years. The commonly used pipeline firstly utilizes conventional image segmentation methods to automatically generate initial masks and then use…

Cited by 0SourceScholar
2018

DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density Estimation

CVPR 2018poster

In real-world crowd counting applications, the crowd densities vary greatly in spatial and temporal domains. A detection based counting method will estimate crowds accurately in low density scenes, while its reliability in congested areas is downgraded. A regression based approach, on the other hand…

Cited by 448SourcePDFScholar
2018

PM-GANs: Discriminative Representation Learning for Action Recognition Using Partial-modalities

ECCV 2018poster

Data of different modalities generally convey complimentary but heterogeneous information, and a more discriminative representation is often preferred by combining multiple data modalities like the RGB and infrared features. However in reality, obtaining both data channels is challenging due to many…

Cited by 32SourcePDFScholar