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08/04/2023
Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP
Open-vocabulary segmentation is a challenging task requiring segmenting ...
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06/29/2023
ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation
This paper presents a new mechanism to facilitate the training of mask t...
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06/12/2023
Compositor: Bottom-up Clustering and Compositing for Robust Part and Object Segmentation
In this work, we present a robust approach for joint part and object seg...
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04/10/2023
Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation
Video Panoptic Segmentation (VPS) aims to achieve comprehensive pixel-le...
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03/30/2023
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision
There has been a recent explosion of computer vision models which perfor...
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01/28/2023
Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans
Human readers or radiologists routinely perform full-body multi-organ mu...
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10/04/2022
MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models
This paper presents MOAT, a family of neural networks that build on top ...
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07/08/2022
k-means Mask Transformer
The rise of transformers in vision tasks not only advances network backb...
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06/17/2022
CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation
We propose Clustering Mask Transformer (CMT-DeepLab), a transformer-base...
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05/30/2022
TubeFormer-DeepLab: Video Mask Transformer
We present TubeFormer-DeepLab, the first attempt to tackle multiple core...
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06/17/2021
DeepLab2: A TensorFlow Library for Deep Labeling
DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a ...
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06/04/2021
Glance-and-Gaze Vision Transformer
Recently, there emerges a series of vision Transformers, which show supe...
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12/12/2020
Mask Guided Matting via Progressive Refinement Network
We propose Mask Guided (MG) Matting, a robust matting framework that tak...
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11/25/2020
Can Temporal Information Help with Contrastive Self-Supervised Learning?
Leveraging temporal information has been regarded as essential for devel...
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10/12/2020
Shape-Texture Debiased Neural Network Training
Shape and texture are two prominent and complementary cues for recognizi...
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04/04/2020
Neural Architecture Search for Lightweight Non-Local Networks
Non-Local (NL) blocks have been widely studied in various vision tasks. ...
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03/28/2020
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Network
3D Convolution Neural Networks (CNNs) have been widely applied to 3D sce...
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03/18/2020
Detecting Pancreatic Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer...
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02/19/2020
When Radiology Report Generation Meets Knowledge Graph
Automatic radiology report generation has been an attracting research pr...
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12/20/2019
C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation
3D convolution neural networks (CNN) have been proved very successful in...
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04/02/2019
Thickened 2D Networks for 3D Medical Image Segmentation
There has been a debate in medical image segmentation on whether to use ...
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09/13/2017
