Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of MichiganUS1.5k papers
- Michigan State UniversityUS1.5k papers
- Centre National de la Recherche ScientifiqueFR1.4k papers
- Lawrence Berkeley National LaboratoryUS1.4k papers
- McGill UniversityCA1.4k papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR1.3k papers
- University of ManchesterGB1.3k papers
- University of LiverpoolGB1.3k papers
- University of TorontoCA1.3k papers
- University of OxfordGB1.3k papers
- TRIUMFCA1.3k papers
- Argonne National LaboratoryUS1.3k papers
12 papers · 2 filters
Roominoes: Generating Novel 3D Floor Plans From Existing 3D Rooms
Kai Wang, Xianghao Xu, Leon Lei +5
Realistic 3D indoor scene datasets have enabled significant recent progress in computer vision, scene understanding, autonomous navigation, and 3D reconstruction. But the scale, di…
Language-Aligned Waypoint (LAW) Supervision for Vision-and-Language Navigation in Continuous Environments
Sonia Raychaudhuri, Saim Wani, Shivansh Patel +2
In the Vision-and-Language Navigation (VLN) task an embodied agent navigates a 3D environment, following natural language instructions. A challenge in this task is how to handle 'o…
One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images
Weina Jin, Xiaoxiao Li, Ghassan Hamarneh
Being able to explain the prediction to clinical end-users is a necessity to leverage the power of AI models for clinical decision support. For medical images, saliency maps are th…
Multimodal Shape Completion via IMLE
Himanshu Arora, Saurabh Mishra, Shichong Peng +2
Shape completion is the problem of completing partial input shapes such as partial scans. This problem finds important applications in computer vision and robotics due to issues su…
Learning Mesh Representations via Binary Space Partitioning Tree Networks
Zhiqin Chen, Andrea Tagliasacchi, Hao Zhang
Polygonal meshes are ubiquitous, but have only played a relatively minor role in the deep learning revolution. State-of-the-art neural generative models for 3D shapes learn implici…
Cascading Modular Network (CAM-Net) for Multimodal Image Synthesis
Shichong Peng, Alireza Moazeni, Ke Li
Deep generative models such as GANs have driven impressive advances in conditional image synthesis in recent years. A persistent challenge has been to generate diverse versions of…
Mirror3D: Depth Refinement for Mirror Surfaces
Jiaqi Tan, Weijie Lin, Angel X. Chang +1
Despite recent progress in depth sensing and 3D reconstruction, mirror surfaces are a significant source of errors. To address this problem, we create the Mirror3D dataset: a 3D mi…
Skin3D: Detection and Longitudinal Tracking of Pigmented Skin Lesions in 3D Total-Body Textured Meshes
Mengliu Zhao, Jeremy Kawahara, Kumar Abhishek +2
We present an automated approach to detect and longitudinally track skin lesions on 3D total-body skin surface scans. The acquired 3D mesh of the subject is unwrapped to a 2D textu…
Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation
Mengyao Zhai, Lei Chen, Jiawei He +3
Humans accumulate knowledge in a lifelong fashion. Modern deep neural networks, on the other hand, are susceptible to catastrophic forgetting: when adapted to perform new tasks, th…
Adaptive Appearance Rendering
Mengyao Zhai, Ruizhi Deng, Jiacheng Chen +3
We propose an approach to generate images of people given a desired appearance and pose. Disentangled representations of pose and appearance are necessary to handle the compound va…
Learning Discriminative Prototypes with Dynamic Time Warping
Xiaobin Chang, Frederick Tung, Greg Mori
Dynamic Time Warping (DTW) is widely used for temporal data processing. However, existing methods can neither learn the discriminative prototypes of different classes nor exploit s…
House-GAN++: Generative Adversarial Layout Refinement Networks
Nelson Nauata, Sepidehsadat Hosseini, Kai-Hung Chang +3
This paper proposes a novel generative adversarial layout refinement network for automated floorplan generation. Our architecture is an integration of a graph-constrained relationa…