research
∙
09/19/2023
Investigating the Catastrophic Forgetting in Multimodal Large Language Models
Following the success of GPT4, there has been a surge in interest in mul...
share
research
∙
07/26/2023
Visual Instruction Inversion: Image Editing via Visual Prompting
Text-conditioned image editing has emerged as a powerful tool for editin...
research
∙
07/25/2023
Benchmarking and Analyzing Generative Data for Visual Recognition
Advancements in large pre-trained generative models have expanded their ...
research
∙
06/29/2023
Generate Anything Anywhere in Any Scene
Text-to-image diffusion models have attracted considerable interest due ...
research
∙
06/09/2023
Leveraging Large Language Models for Scalable Vector Graphics-Driven Image Understanding
Recently, large language models (LLMs) have made significant advancement...
research
∙
04/17/2023
Visual Instruction Tuning
Instruction tuning large language models (LLMs) using machine-generated ...
research
∙
03/13/2023
InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning
Recent state-of-the-art methods in imbalanced semi-supervised learning (...
research
∙
02/20/2023
Towards Universal Fake Image Detectors that Generalize Across Generative Models
With generative models proliferating at a rapid rate, there is a growing...
research
∙
01/17/2023
Learning Customized Visual Models with Retrieval-Augmented Knowledge
Image-text contrastive learning models such as CLIP have demonstrated st...
research
∙
01/17/2023
GLIGEN: Open-Set Grounded Text-to-Image Generation
Large-scale text-to-image diffusion models have made amazing advances. H...
research
∙
12/21/2022
Generalized Decoding for Pixel, Image, and Language
We present X-Decoder, a generalized decoding model that can predict pixe...
research
∙
12/09/2022
Expeditious Saliency-guided Mix-up through Random Gradient Thresholding
Mix-up training approaches have proven to be effective in improving the ...
research
∙
11/04/2022
Contrastive Learning for Diverse Disentangled Foreground Generation
We introduce a new method for diverse foreground generation with explici...
research
∙
06/13/2022
EnergyMatch: Energy-based Pseudo-Labeling for Semi-Supervised Learning
Recent state-of-the-art methods in semi-supervised learning (SSL) combin...
research
∙
05/31/2022
What Knowledge Gets Distilled in Knowledge Distillation?
Knowledge distillation aims to transfer useful information from a teache...
research
∙
04/19/2022
ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models
Learning visual representations from natural language supervision has re...
research
∙
04/09/2022
The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization
Training with an emphasis on "hard-to-learn" components of the data has ...
research
∙
04/06/2022
End-to-End Instance Edge Detection
Edge detection has long been an important problem in the field of comput...
research
∙
03/28/2022
GIRAFFE HD: A High-Resolution 3D-aware Generative Model
3D-aware generative models have shown that the introduction of 3D inform...
research
∙
03/21/2022
Masked Discrimination for Self-Supervised Learning on Point Clouds
Masked autoencoding has achieved great success for self-supervised learn...
research
∙
10/08/2021
Collaging Class-specific GANs for Semantic Image Synthesis
We propose a new approach for high resolution semantic image synthesis. ...
research
∙
08/30/2021
Equine Pain Behavior Classification via Self-Supervised Disentangled Pose Representation
Timely detection of horse pain is important for equine welfare. Horses e...
research
∙
04/13/2021
Few-shot Image Generation via Cross-domain Correspondence
Training generative models, such as GANs, on a target domain containing ...
research
∙
04/08/2021
Progressive Temporal Feature Alignment Network for Video Inpainting
Video inpainting aims to fill spatio-temporal "corrupted" regions with p...
research
∙
04/05/2021
Generating Furry Cars: Disentangling Object Shape Appearance across Multiple Domains
We consider the novel task of learning disentangled representations of o...
research
∙
12/22/2020
YolactEdge: Real-time Instance Segmentation on the Edge (Jetson AGX Xavier: 30 FPS, RTX 2080 Ti: 170 FPS)
We propose YolactEdge, the first competitive instance segmentation appro...
research
∙
08/21/2020
Delving Deeper into Anti-aliasing in ConvNets
Aliasing refers to the phenomenon that high frequency signals degenerate...
research
∙
04/09/2020
Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection
Weakly supervised learning has emerged as a compelling tool for object d...
research
∙
02/04/2020
Action Graphs: Weakly-supervised Action Localization with Graph Convolution Networks
We present a method for weakly-supervised action localization based on g...
research
∙
01/23/2020
Audiovisual SlowFast Networks for Video Recognition
We present Audiovisual SlowFast Networks, an architecture for integrated...
research
∙
01/09/2020
Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias
Existing models often leverage co-occurrences between objects and their ...
research
∙
12/03/2019
YOLACT++: Better Real-time Instance Segmentation
We present a simple, fully-convolutional model for real-time (>30 fps) i...
research
∙
11/26/2019
Password-conditioned Anonymization and Deanonymization with Face Identity Transformers
Cameras are prevalent in our daily lives, and enable many useful systems...
research
∙
11/26/2019
MixNMatch: Multifactor Disentanglement and Encodingfor Conditional Image Generation
We present MixNMatch, a conditional generative model that learns to dise...
research
∙
11/26/2019
MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation
We present MixNMatch, a conditional generative model that learns to dise...
research
∙
10/01/2019
Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Imbalanced Data
We propose a novel unsupervised generative model, Elastic-InfoGAN, that ...
research
∙
06/12/2019
HPLFlowNet: Hierarchical Permutohedral Lattice FlowNet for Scene Flow Estimation on Large-scale Point Clouds
We present a novel deep neural network architecture for end-to-end scene...
research
∙
04/04/2019
YOLACT: Real-time Instance Segmentation
We present a simple, fully-convolutional model for real-time instance se...
research
∙
11/27/2018
FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery
We propose FineGAN, a novel unsupervised GAN framework, which disentangl...
research
∙
11/06/2018
Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and Beyond
We propose 'Hide-and-Seek' a general purpose data augmentation technique...
research
∙
08/24/2018
A Visual Attention Grounding Neural Model for Multimodal Machine Translation
We introduce a novel multimodal machine translation model that utilizes ...
research
∙
04/03/2018
Transferring Common-Sense Knowledge for Object Detection
We propose the idea of transferring common-sense knowledge from source c...
research
∙
03/30/2018
Learning to Anonymize Faces for Privacy Preserving Action Detection
There is an increasing concern in computer vision devices invading the p...
research
∙
12/18/2017
Spatial-Temporal Memory Networks for Video Object Detection
We introduce Spatial-Temporal Memory Networks (STMN) for video object de...
research
∙
11/24/2017
Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery
In human learning, it is common to use multiple sources of information j...
research
∙
05/25/2017
Who Will Share My Image? Predicting the Content Diffusion Path in Online Social Networks
Content popularity prediction has been extensively studied due to its im...
research
∙
05/03/2017
Weakly-supervised Visual Grounding of Phrases with Linguistic Structures
We propose a weakly-supervised approach that takes image-sentence pairs ...
research
∙
08/09/2016
End-to-End Localization and Ranking for Relative Attributes
We propose an end-to-end deep convolutional network to simultaneously lo...
research
∙
04/19/2016
Track and Transfer: Watching Videos to Simulate Strong Human Supervision for Weakly-Supervised Object Detection
The status quo approach to training object detectors requires expensive ...
research
∙
06/25/2014