A. Yuille

3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose Estimation

Yi Zhang, Pengliang Ji, Angtian Wang +3

Regression-based methods for 3D human pose estimation directly predict the 3D pose parameters from a 2D image using deep networks. While achieving state-of-the-art performance on s…

Animal3D: A Comprehensive Dataset of 3D Animal Pose and Shape

Jiacong Xu, Yi Zhang, Jiawei Peng +17

Accurately estimating the 3D pose and shape is an essential step towards understanding animal behavior, and can potentially benefit many downstream applications, such as wildlife c…

SwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentation

Yiqing Wang, Zihan Li, Jieru Mei +7

Recent advancements in large-scale Vision Transformers have made significant strides in improving pre-trained models for medical image segmentation. However, these methods face a n…

Generating Images with 3D Annotations Using Diffusion Models

Wufei Ma, Qihao Liu, Jiahao Wang +11

Diffusion models have emerged as a powerful generative method, capable of producing stunning photo-realistic images from natural language descriptions. However, these models lack e…

Compositor: Bottom-up Clustering and Compositing for Robust Part and Object Segmentation

Ju He, Jieneng Chen, Ming-Xian Lin +2

In this work, we present a robust approach for joint part and object segmentation. Specifically, we reformulate object and part segmentation as an optimization problem and build a…

Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search

Qihao Liu, Adam Kortylewski, Yutong Bai +2

Text-guided diffusion models (TDMs) are widely applied but can fail unexpectedly. Common failures include: (i) natural-looking text prompts generating images with the wrong content…

Neural Textured Deformable Meshes for Robust Analysis-by-Synthesis

Angtian Wang, Wufei Ma, Alan Yuille +1

Human vision demonstrates higher robustness than current AI algorithms under out-of-distribution scenarios. It has been conjectured such robustness benefits from performing analysi…

Robust Category-Level 3D Pose Estimation from Synthetic Data

Jiahao Yang, Wufei Ma, Angtian Wang +3

Obtaining accurate 3D object poses is vital for numerous computer vision applications, such as 3D reconstruction and scene understanding. However, annotating real-world objects is…

NOVUM: Neural Object Volumes for Robust Object Classification

Artur Jesslen, Guofeng Zhang, Angtian Wang +3

Discriminative models for object classification typically learn image-based representations that do not capture the compositional and 3D nature of objects. In this work, we show th…

Diffusion Models as Masked Autoencoders

Chen Wei, Karttikeya Mangalam, Po-Yao Huang +7

There has been a longstanding belief that generation can facilitate a true understanding of visual data. In line with this, we revisit generatively pre-training visual representati…

OOD-CV-v2: An extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images

Bingchen Zhao, Jiahao Wang, Wufei Ma +7

Enhancing the robustness of vision algorithms in real-world scenarios is challenging. One reason is that existing robustness benchmarks are limited, as they either rely on syntheti…

InstMove: Instance Motion for Object-centric Video Segmentation

Qihao Liu, Junfeng Wu, Yi Jiang +3

Despite significant efforts, cutting-edge video segmentation methods still remain sensitive to occlusion and rapid movement, due to their reliance on the appearance of objects in t…

PoseExaminer: Automated Testing of Out-of-Distribution Robustness in Human Pose and Shape Estimation

Qihao Liu, Adam Kortylewski, Alan Yuille

Human pose and shape (HPS) estimation methods achieve remarkable results. However, current HPS benchmarks are mostly designed to test models in scenarios that are similar to the tr…