research
∙
08/19/2023
3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose Estimation
Regression-based methods for 3D human pose estimation directly predict t...
share
research
∙
08/06/2023
Early Detection and Localization of Pancreatic Cancer by Label-Free Tumor Synthesis
Early detection and localization of pancreatic cancer can increase the 5...
research
∙
06/13/2023
Adding 3D Geometry Control to Diffusion Models
Diffusion models have emerged as a powerful method of generative modelin...
research
∙
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...
research
∙
06/01/2023
Continual Learning for Abdominal Multi-Organ and Tumor Segmentation
The ability to dynamically extend a model to new data and classes is cri...
research
∙
06/01/2023
Intriguing Properties of Text-guided Diffusion Models
Text-guided diffusion models (TDMs) are widely applied but can fail unex...
research
∙
05/31/2023
Neural Textured Deformable Meshes for Robust Analysis-by-Synthesis
Human vision demonstrates higher robustness than current AI algorithms u...
research
∙
05/25/2023
Robust Category-Level 3D Pose Estimation from Synthetic Data
Obtaining accurate 3D object poses is vital for numerous computer vision...
research
∙
05/24/2023
Robust 3D-aware Object Classification via Discriminative Render-and-Compare
In real-world applications, it is essential to jointly estimate the 3D o...
research
∙
05/16/2023
Annotating 8,000 Abdominal CT Volumes for Multi-Organ Segmentation in Three Weeks
Annotating medical images, particularly for organ segmentation, is labor...
research
∙
04/17/2023
OOD-CV-v2: An extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images
Enhancing the robustness of vision algorithms in real-world scenarios is...
research
∙
04/06/2023
Diffusion Models as Masked Autoencoders
There has been a longstanding belief that generation can facilitate a tr...
research
∙
03/27/2023
Label-Free Liver Tumor Segmentation
We demonstrate that AI models can accurately segment liver tumors withou...
research
∙
03/14/2023
InstMove: Instance Motion for Object-centric Video Segmentation
Despite significant efforts, cutting-edge video segmentation methods sti...
research
∙
03/13/2023
PoseExaminer: Automated Testing of Out-of-Distribution Robustness in Human Pose and Shape Estimation
Human pose and shape (HPS) estimation methods achieve remarkable results...
research
∙
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...
research
∙
01/02/2023
CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection
An increasing number of public datasets have shown a marked clinical imp...
research
∙
01/02/2023
Learning Road Scene-level Representations via Semantic Region Prediction
In this work, we tackle two vital tasks in automated driving systems, i....
research
∙
12/20/2022
Unleashing the Power of Visual Prompting At the Pixel Level
This paper presents a simple and effective visual prompting method for a...
research
∙
12/07/2022
AsyInst: Asymmetric Affinity with DepthGrad and Color for Box-Supervised Instance Segmentation
The weakly supervised instance segmentation is a challenging task. The e...
research
∙
12/01/2022
Localization vs. Semantics: How Can Language Benefit Visual Representation Learning?
Despite the superior performance brought by vision-and-language pretrain...
research
∙
12/01/2022
Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoning
Visual Question Answering (VQA) models often perform poorly on out-of-di...
research
∙
11/29/2022
LUMix: Improving Mixup by Better Modelling Label Uncertainty
Modern deep networks can be better generalized when trained with noisy s...
research
∙
11/21/2022
SMAUG: Sparse Masked Autoencoder for Efficient Video-Language Pre-training
Video-language pre-training is crucial for learning powerful multi-modal...
research
∙
10/26/2022
Synthetic Tumors Make AI Segment Tumors Better
We develop a novel strategy to generate synthetic tumors. Unlike existin...
research
∙
10/23/2022
1st Place Solution of The Robust Vision Challenge (RVC) 2022 Semantic Segmentation Track
This report describes the winning solution to the semantic segmentation ...
research
∙
10/23/2022
Delving into Masked Autoencoders for Multi-Label Thorax Disease Classification
Vision Transformer (ViT) has become one of the most popular neural archi...
research
∙
10/21/2022
Context-Enhanced Stereo Transformer
Stereo depth estimation is of great interest for computer vision researc...
research
∙
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 ...
research
∙
09/12/2022
Robust Category-Level 6D Pose Estimation with Coarse-to-Fine Rendering of Neural Features
We consider the problem of category-level 6D pose estimation from a sing...
research
∙
08/25/2022
Masked Autoencoders Enable Efficient Knowledge Distillers
This paper studies the potential of distilling knowledge from pre-traine...
research
∙
07/29/2022
Explicit Occlusion Reasoning for Multi-person 3D Human Pose Estimation
Occlusion poses a great threat to monocular multi-person 3D human pose e...
research
∙
07/21/2022
In Defense of Online Models for Video Instance Segmentation
In recent years, video instance segmentation (VIS) has been largely adva...
research
∙
07/08/2022
k-means Mask Transformer
The rise of transformers in vision tasks not only advances network backb...
research
∙
07/06/2022
Unsupervised Domain Adaptation through Shape Modeling for Medical Image Segmentation
Shape information is a strong and valuable prior in segmenting organs in...
research
∙
06/17/2022
CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation
We propose Clustering Mask Transformer (CMT-DeepLab), a transformer-base...
research
∙
06/15/2022
A Simple Data Mixing Prior for Improving Self-Supervised Learning
Data mixing (e.g., Mixup, Cutmix, ResizeMix) is an essential component f...
research
∙
05/30/2022
VoGE: A Differentiable Volume Renderer using Gaussian Ellipsoids for Analysis-by-Synthesis
Differentiable rendering allows the application of computer graphics on ...
research
∙
05/03/2022
In Defense of Image Pre-Training for Spatiotemporal Recognition
Image pre-training, the current de-facto paradigm for a wide range of vi...
research
∙
04/21/2022
Fast AdvProp
Adversarial Propagation (AdvProp) is an effective way to improve recogni...
research
∙
04/05/2022
SwapMix: Diagnosing and Regularizing the Over-Reliance on Visual Context in Visual Question Answering
While Visual Question Answering (VQA) has progressed rapidly, previous w...
research
∙
03/22/2022
CP2: Copy-Paste Contrastive Pretraining for Semantic Segmentation
Recent advances in self-supervised contrastive learning yield good image...
research
∙
02/09/2022
Point-Level Region Contrast for Object Detection Pre-Training
In this work we present point-level region contrast, a self-supervised p...
research
∙
12/20/2021
Lite Vision Transformer with Enhanced Self-Attention
Despite the impressive representation capacity of vision transformer mod...
research
∙
12/16/2021
Masked Feature Prediction for Self-Supervised Visual Pre-Training
We present Masked Feature Prediction (MaskFeat) for self-supervised pre-...
research
∙
12/03/2021
MT-TransUNet: Mediating Multi-Task Tokens in Transformers for Skin Lesion Segmentation and Classification
Recent advances in automated skin cancer diagnosis have yielded performa...
research
∙
12/02/2021
PartImageNet: A Large, High-Quality Dataset of Parts
A part-based object understanding facilitates efficient compositional le...
research
∙
11/29/2021
ROBIN : A Benchmark for Robustness to Individual Nuisances in Real-World Out-of-Distribution Shifts
Enhancing the robustness in real-world scenarios has been proven very ch...
research
∙
11/25/2021
Learning from Temporal Gradient for Semi-supervised Action Recognition
Semi-supervised video action recognition tends to enable deep neural net...
research
∙
11/18/2021
