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05/31/2023
Dense and Aligned Captions (DAC) Promote Compositional Reasoning in VL Models
Vision and Language (VL) models offer an effective method for aligning r...
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03/30/2023
Going Beyond Nouns With Vision Language Models Using Synthetic Data
Large-scale pre-trained Vision Language (VL) models have shown remar...
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03/16/2023
Neural Architecture Search for Effective Teacher-Student Knowledge Transfer in Language Models
Large pre-trained language models have achieved state-of-the-art results...
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03/15/2023
MAtch, eXpand and Improve: Unsupervised Finetuning for Zero-Shot Action Recognition with Language Knowledge
Large scale Vision-Language (VL) models have shown tremendous success in...
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03/06/2023
Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning
Prompt tuning, in which a base pretrained model is adapted to each task ...
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03/02/2023
Learning to Grow Pretrained Models for Efficient Transformer Training
Scaling transformers has led to significant breakthroughs in many domain...
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02/14/2023
Energy Transformer
Transformers have become the de facto models of choice in machine learni...
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12/19/2022
Synthetic Pre-Training Tasks for Neural Machine Translation
Pre-training is an effective technique for ensuring robust performance o...
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11/23/2022
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning
Computer vision models suffer from a phenomenon known as catastrophic fo...
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11/21/2022
Teaching Structured Vision Language Concepts to Vision Language Models
Vision and Language (VL) models have demonstrated remarkable zero-shot p...
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11/17/2022
ConStruct-VL: Data-Free Continual Structured VL Concepts Learning
Recently, large-scale pre-trained Vision-and-Language (VL) foundation mo...
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10/18/2022
Semi-Supervised Domain Adaptation with Auto-Encoder via Simultaneous Learning
We present a new semi-supervised domain adaptation framework that combin...
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09/08/2022
FETA: Towards Specializing Foundation Models for Expert Task Applications
Foundation Models (FMs) have demonstrated unprecedented capabilities inc...
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05/31/2022
VALHALLA: Visual Hallucination for Machine Translation
Designing better machine translation systems by considering auxiliary in...
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11/30/2021
Task2Sim : Towards Effective Pre-training and Transfer from Synthetic Data
Pre-training models on Imagenet or other massive datasets of real images...
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11/08/2021
Cascaded Multilingual Audio-Visual Learning from Videos
In this paper, we explore self-supervised audio-visual models that learn...
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10/28/2021
Selective Regression Under Fairness Criteria
Selective regression allows abstention from prediction if the confidence...
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10/28/2021
Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing
Unsupervised domain adaptation which aims to adapt models trained on a l...
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08/23/2021
Dynamic Network Quantization for Efficient Video Inference
Deep convolutional networks have recently achieved great success in vide...
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06/26/2021
An Image Classifier Can Suffice For Video Understanding
We propose a new perspective on video understanding by casting the video...
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06/23/2021
IA-RED^2: Interpretability-Aware Redundancy Reduction for Vision Transformers
The self-attention-based model, transformer, is recently becoming the le...
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06/14/2021
Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data
Most existing works in few-shot learning rely on meta-learning the netwo...
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06/04/2021
RegionViT: Regional-to-Local Attention for Vision Transformers
Vision transformer (ViT) has recently showed its strong capability in ac...
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05/11/2021
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition
Multi-modal learning, which focuses on utilizing various modalities to i...
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04/26/2021
Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos
Multimodal self-supervised learning is getting more and more attention a...
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04/20/2021
Detector-Free Weakly Supervised Grounding by Separation
Nowadays, there is an abundance of data involving images and surrounding...
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03/27/2021
CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
The recently developed vision transformer (ViT) has achieved promising r...
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03/24/2021
A Broad Study on the Transferability of Visual Representations with Contrastive Learning
Tremendous progress has been made in visual representation learning, not...
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03/02/2021
All at Once Network Quantization via Collaborative Knowledge Transfer
Network quantization has rapidly become one of the most widely used meth...
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02/15/2021
VA-RED^2: Video Adaptive Redundancy Reduction
Performing inference on deep learning models for videos remains a challe...
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02/10/2021
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition
Temporal modelling is the key for efficient video action recognition. Wh...
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02/04/2021
Semi-Supervised Action Recognition with Temporal Contrastive Learning
Learning to recognize actions from only a handful of labeled videos is a...
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12/30/2020
A Maximal Correlation Approach to Imposing Fairness in Machine Learning
As machine learning algorithms grow in popularity and diversify to many ...
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12/06/2020
Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation
Partial domain adaptation which assumes that the unknown target label sp...
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11/20/2020
Large Scale Neural Architecture Search with Polyharmonic Splines
Neural Architecture Search (NAS) is a powerful tool to automatically des...
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10/22/2020
Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition
In recent years, a number of approaches based on 2D CNNs and 3D CNNs hav...
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08/26/2020
Measurement-driven Security Analysis of Imperceptible Impersonation Attacks
The emergence of Internet of Things (IoT) brings about new security chal...
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08/13/2020
Adversarial Knowledge Transfer from Unlabeled Data
While machine learning approaches to visual recognition offer great prom...
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08/12/2020
Mitigating Dataset Imbalance via Joint Generation and Classification
Supervised deep learning methods are enjoying enormous success in many p...
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07/31/2020
AR-Net: Adaptive Frame Resolution for Efficient Action Recognition
Action recognition is an open and challenging problem in computer vision...
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07/22/2020
Camera On-boarding for Person Re-identification using Hypothesis Transfer Learning
Most of the existing approaches for person re-identification consider a ...
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06/23/2020
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search
Neural Architecture Search (NAS) is an open and challenging problem in m...
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03/21/2020
Non-Adversarial Video Synthesis with Learned Priors
Most of the existing works in video synthesis focus on generating videos...
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11/27/2019
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
Multi-task learning is an open and challenging problem in computer visio...
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10/29/2019
Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets
Recent advances in computer vision and deep learning have led to breakth...
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08/27/2019
Consistent Cross-view Matching for Unsupervised Person Re-identification
Most existing unsupervised person re-identificationmethods focus on lear...
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08/23/2018
Webly Supervised Joint Embedding for Cross-Modal Image-Text Retrieval
Cross-modal retrieval between visual data and natural language descripti...
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08/07/2018
Contemplating Visual Emotions: Understanding and Overcoming Dataset Bias
While machine learning approaches to visual emotion recognition offer gr...
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05/08/2018
FFNet: Video Fast-Forwarding via Reinforcement Learning
For many applications with limited computation, communication, storage a...
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06/09/2017