1.2k citations · 7.7k across the 159 of their papers we have counts for
18 papers · 1 filter
SKU-Patch: Towards Efficient Instance Segmentation for Unseen Objects in Auto-Store
Biqi Yang, Weiliang Tang, Xiaojie Gao +4
In large-scale storehouses, precise instance masks are crucial for robotic bin picking but are challenging to obtain. Existing instance segmentation methods typically rely on a ted…
MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentation
Cheng Chen, Juzheng Miao, Dufan Wu +10
The Segment Anything Model (SAM), a foundation model for general image segmentation, has demonstrated impressive zero-shot performance across numerous natural image segmentation ta…
Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following
Ziyu Guo, Renrui Zhang, Xiangyang Zhu +8
We introduce Point-Bind, a 3D multi-modality model aligning point clouds with 2D image, language, audio, and video. Guided by ImageBind, we construct a joint embedding space betwee…
Distribution-Aware Calibration for Object Detection with Noisy Bounding Boxes
Donghao Zhou, Jialin Li, Jinpeng Li +7
Large-scale well-annotated datasets are of great importance for training an effective object detector. However, obtaining accurate bounding box annotations is laborious and demandi…
Unite-Divide-Unite: Joint Boosting Trunk and Structure for High-accuracy Dichotomous Image Segmentation
Jialun Pei, Zhangjun Zhou, Yueming Jin +2
High-accuracy Dichotomous Image Segmentation (DIS) aims to pinpoint category-agnostic foreground objects from natural scenes. The main challenge for DIS involves identifying the hi…
SDF-Pack: Towards Compact Bin Packing with Signed-Distance-Field Minimization
Jia-Hui Pan, Ka-Hei Hui, Xiaojie Gao +4
Robotic bin packing is very challenging, especially when considering practical needs such as object variety and packing compactness. This paper presents SDF-Pack, a new approach ba…
CalibNet: Dual-branch Cross-modal Calibration for RGB-D Salient Instance Segmentation
Jialun Pei, Tao Jiang, He Tang +4
We propose a novel approach for RGB-D salient instance segmentation using a dual-branch cross-modal feature calibration architecture called CalibNet. Our method simultaneously cali…
3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation
Shizhan Gong, Yuan Zhong, Wenao Ma +5
Despite that the segment anything model (SAM) achieved impressive results on general-purpose semantic segmentation with strong generalization ability on daily images, its demonstra…
Deep Omni-supervised Learning for Rib Fracture Detection from Chest Radiology Images
Zhizhong Chai, Luyang Luo, Huangjing Lin +2
Deep learning (DL)-based rib fracture detection has shown promise of playing an important role in preventing mortality and improving patient outcome. Normally, developing DL-based…
Scale-aware Super-resolution Network with Dual Affinity Learning for Lesion Segmentation from Medical Images
Yanwen Li, Luyang Luo, Huangjing Lin +2
Convolutional Neural Networks (CNNs) have shown remarkable progress in medical image segmentation. However, lesion segmentation remains a challenge to state-of-the-art CNN-based al…
DPPMask: Masked Image Modeling with Determinantal Point Processes
Junde Xu, Zikai Lin, Donghao Zhou +5
Masked Image Modeling (MIM) has achieved impressive representative performance with the aim of reconstructing randomly masked images. Despite the empirical success, most previous w…
Video Dehazing via a Multi-Range Temporal Alignment Network with Physical Prior
Jiaqi Xu, Xiaowei Hu, Lei Zhu +4
Video dehazing aims to recover haze-free frames with high visibility and contrast. This paper presents a novel framework to effectively explore the physical haze priors and aggrega…
Traj-MAE: Masked Autoencoders for Trajectory Prediction
Hao Chen, Jiaze Wang, Kun Shao +5
Trajectory prediction has been a crucial task in building a reliable autonomous driving system by anticipating possible dangers. One key issue is to generate consistent trajectory…
PointPatchMix: Point Cloud Mixing with Patch Scoring
Yi Wang, Jiaze Wang, Jinpeng Li +4
Data augmentation is an effective regularization strategy for mitigating overfitting in deep neural networks, and it plays a crucial role in 3D vision tasks, where the point cloud…
DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and Reconstruction
Bowen Wang, Chen Liang, Jiaze Wang +7
Attaining the equilibrium state of a catalyst-adsorbate system is key to fundamentally assessing its effective properties, such as adsorption energy. Machine learning methods with…
Adaptive Negative Evidential Deep Learning for Open-set Semi-supervised Learning
Yang Yu, Danruo Deng, Furui Liu +4
Semi-supervised learning (SSL) methods assume that labeled data, unlabeled data and test data are from the same distribution. Open-set semi-supervised learning (Open-set SSL) consi…
Uncertainty Estimation by Fisher Information-based Evidential Deep Learning
Danruo Deng, Guangyong Chen, Yang Yu +2
Uncertainty estimation is a key factor that makes deep learning reliable in practical applications. Recently proposed evidential neural networks explicitly account for different un…
Joint-MAE: 2D-3D Joint Masked Autoencoders for 3D Point Cloud Pre-training
Ziyu Guo, Renrui Zhang, Longtian Qiu +2
Masked Autoencoders (MAE) have shown promising performance in self-supervised learning for both 2D and 3D computer vision. However, existing MAE-style methods can only learn from t…