research
∙
05/25/2023
Making Vision Transformers Truly Shift-Equivariant
For computer vision tasks, Vision Transformers (ViTs) have become one of...
share
research
∙
12/19/2022
GeoCode: Interpretable Shape Programs
Mapping high-fidelity 3D geometry to a representation that allows for in...
research
∙
12/01/2022
Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation
A diffusion model learns to predict a vector field of gradients. We prop...
research
∙
10/14/2022
Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks
We propose learnable polyphase sampling (LPS), a pair of learnable down/...
research
∙
10/11/2022
TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generation
We present TetGAN, a convolutional neural network designed to generate t...
research
∙
09/08/2022
Text-Free Learning of a Natural Language Interface for Pretrained Face Generators
We propose Fast text2StyleGAN, a natural language interface that adapts ...
research
∙
04/07/2022
Adapting CLIP For Phrase Localization Without Further Training
Supervised or weakly supervised methods for phrase localization (textual...
research
∙
04/07/2022
Total Variation Optimization Layers for Computer Vision
Optimization within a layer of a deep-net has emerged as a new direction...
research
∙
04/07/2022
Equivariance Discovery by Learned Parameter-Sharing
Designing equivariance as an inductive bias into deep-nets has been a pr...
research
∙
08/06/2021
Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning
Solving complex real-world tasks, e.g., autonomous fleet control, often ...
research
∙
07/23/2021
Cooperative Exploration for Multi-Agent Deep Reinforcement Learning
Exploration is critical for good results in deep reinforcement learning ...
research
∙
06/13/2021
Inverting Adversarially Robust Networks for Image Synthesis
Recent research in adversarially robust classifiers suggests their repre...
research
∙
05/18/2021
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data
Extracting detailed 3D information of objects from video data is an impo...
research
∙
12/17/2020
High-Throughput Synchronous Deep RL
Deep reinforcement learning (RL) is computationally demanding and requir...
research
∙
07/02/2020
Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning
Existing semi-supervised learning (SSL) algorithms use a single weight t...
research
∙
10/31/2019
Chirality Nets for Human Pose Regression
We propose Chirality Nets, a family of deep nets that is equivariant to ...
research
∙
10/31/2019
PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning
Sample efficiency and scalability to a large number of agents are two im...
research
∙
11/21/2018
Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection
Fine-grained action detection is an important task with numerous applica...
research
∙
03/29/2018
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts
Textual grounding is an important but challenging task for human-compute...
research
∙
03/29/2018
Unsupervised Textual Grounding: Linking Words to Image Concepts
Textual grounding, i.e., linking words to objects in images, is a challe...
research
∙
02/08/2017
Video Frame Synthesis using Deep Voxel Flow
We address the problem of synthesizing new video frames in an existing v...
research
∙
07/26/2016
