research
∙
09/16/2023
Dual-Camera Joint Deblurring-Denoising
Recent image enhancement methods have shown the advantages of using a pa...
share
research
∙
08/17/2023
Watch Your Steps: Local Image and Scene Editing by Text Instructions
Denoising diffusion models have enabled high-quality image generation an...
research
∙
04/26/2023
StepFormer: Self-supervised Step Discovery and Localization in Instructional Videos
Instructional videos are an important resource to learn procedural tasks...
research
∙
04/21/2023
Long-Term Photometric Consistent Novel View Synthesis with Diffusion Models
Novel view synthesis from a single input image is a challenging task, wh...
research
∙
04/19/2023
Reference-guided Controllable Inpainting of Neural Radiance Fields
The popularity of Neural Radiance Fields (NeRFs) for view synthesis has ...
research
∙
11/22/2022
SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting with Neural Radiance Fields
Neural Radiance Fields (NeRFs) have emerged as a popular approach for no...
research
∙
11/03/2022
Quantifying and Learning Static vs. Dynamic Information in Deep Spatiotemporal Networks
There is limited understanding of the information captured by deep spati...
research
∙
10/31/2022
SAGE: Saliency-Guided Mixup with Optimal Rearrangements
Data augmentation is a key element for training accurate models by reduc...
research
∙
06/06/2022
A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying Static vs. Dynamic Information
Deep spatiotemporal models are used in a variety of computer vision task...
research
∙
05/04/2022
P3IV: Probabilistic Procedure Planning from Instructional Videos with Weak Supervision
In this paper, we study the problem of procedure planning in instruction...
research
∙
04/20/2022
Uncertainty-based Cross-Modal Retrieval with Probabilistic Representations
Probabilistic embeddings have proven useful for capturing polysemous wor...
research
∙
04/12/2022
Semantic keypoint-based pose estimation from single RGB frames
This paper presents an approach to estimating the continuous 6-DoF pose ...
research
∙
03/27/2022
Temporal Transductive Inference for Few-Shot Video Object Segmentation
Few-shot video object segmentation (FS-VOS) aims at segmenting video fra...
research
∙
10/20/2021
Simpler Does It: Generating Semantic Labels with Objectness Guidance
Existing weakly or semi-supervised semantic segmentation methods utilize...
research
∙
08/26/2021
Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers
In this work, we consider the problem of sequence-to-sequence alignment ...
research
∙
08/23/2021
SegMix: Co-occurrence Driven Mixup for Semantic Segmentation and Adversarial Robustness
In this paper, we present a strategy for training convolutional neural n...
research
∙
08/17/2021
Global Pooling, More than Meets the Eye: Position Information is Encoded Channel-Wise in CNNs
In this paper, we challenge the common assumption that collapsing the sp...
research
∙
05/11/2021
Representation Learning via Global Temporal Alignment and Cycle-Consistency
We introduce a weakly supervised method for representation learning base...
research
∙
05/10/2021
Stochastic Image-to-Video Synthesis using cINNs
Video understanding calls for a model to learn the characteristic interp...
research
∙
01/28/2021
Position, Padding and Predictions: A Deeper Look at Position Information in CNNs
In contrast to fully connected networks, Convolutional Neural Networks (...
research
∙
01/27/2021
Shape or Texture: Understanding Discriminative Features in CNNs
Contrasting the previous evidence that neurons in the later layers of a ...
research
∙
11/16/2020
Cycle-Consistent Generative Rendering for 2D-3D Modality Translation
For humans, visual understanding is inherently generative: given a 3D sh...
research
∙
10/26/2020
Wavelet Flow: Fast Training of High Resolution Normalizing Flows
Normalizing flows are a class of probabilistic generative models which a...
research
∙
08/13/2020
Feature Binding with Category-Dependant MixUp for Semantic Segmentation and Adversarial Robustness
In this paper, we present a strategy for training convolutional neural n...
research
∙
03/25/2020
Learning to Correct Overexposed and Underexposed Photos
Capturing photographs with wrong exposures remains a major source of err...
research
∙
04/17/2019
End-to-End Learning of Representations for Asynchronous Event-Based Data
Event cameras are vision sensors that record asynchronous streams of per...
research
∙
01/16/2019
UAN: Unified Attention Network for Convolutional Neural Networks
We propose a new architecture that learns to attend to different Convolu...
research
∙
06/25/2018
Unsupervised Learning of Sensorimotor Affordances by Stochastic Future Prediction
Recently, much progress has been made building systems that can capture ...
research
∙
03/26/2018
Predicting the Future with Transformational States
An intelligent observer looks at the world and sees not only what is, bu...
research
∙
06/21/2017
Two-Stream Convolutional Networks for Dynamic Texture Synthesis
We introduce a two-stream model for dynamic texture synthesis. Our model...
research
∙
03/14/2017
6-DoF Object Pose from Semantic Keypoints
This paper presents a novel approach to estimating the continuous six de...
research
∙
02/23/2017
Building Usage Profiles Using Deep Neural Nets
To improve software quality, one needs to build test scenarios resemblin...
research
∙
11/23/2016
Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human Pose
This paper addresses the challenge of 3D human pose estimation from a si...
research
∙
08/20/2016
Back to Basics: Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
Recently, convolutional networks (convnets) have proven useful for predi...
research
∙
11/13/2015
Learning Dense Convolutional Embeddings for Semantic Segmentation
This paper proposes a new deep convolutional neural network (DCNN) archi...
research
∙
02/25/2015