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09/13/2023
TAP: Targeted Prompting for Task Adaptive Generation of Textual Training Instances for Visual Classification
Vision and Language Models (VLMs), such as CLIP, have enabled visual rec...
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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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05/29/2023
LaFTer: Label-Free Tuning of Zero-shot Classifier using Language and Unlabeled Image Collections
Recently, large-scale pre-trained Vision and Language (VL) models have s...
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05/21/2023
Comparison of Multilingual Self-Supervised and Weakly-Supervised Speech Pre-Training for Adaptation to Unseen Languages
Recent models such as XLS-R and Whisper have made multilingual speech te...
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05/10/2023
Incorporating Structured Representations into Pretrained Vision Language Models Using Scene Graphs
Vision and Language (VL) models have demonstrated remarkable zero-shot p...
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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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03/29/2023
What, when, and where? – Self-Supervised Spatio-Temporal Grounding in Untrimmed Multi-Action Videos from Narrated Instructions
Spatio-temporal grounding describes the task of localizing events in spa...
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03/26/2023
Mind the Backbone: Minimizing Backbone Distortion for Robust Object Detection
Building object detectors that are robust to domain shifts is critical f...
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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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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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11/29/2022
Procedural Image Programs for Representation Learning
Learning image representations using synthetic data allows training neur...
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11/27/2022
Exploring Consistency in Cross-Domain Transformer for Domain Adaptive Semantic Segmentation
While transformers have greatly boosted performance in semantic segmenta...
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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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10/07/2022
C2KD: Cross-Lingual Cross-Modal Knowledge Distillation for Multilingual Text-Video Retrieval
Multilingual text-video retrieval methods have improved significantly in...
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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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03/31/2022
SimVQA: Exploring Simulated Environments for Visual Question Answering
Existing work on VQA explores data augmentation to achieve better genera...
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12/08/2021
Everything at Once – Multi-modal Fusion Transformer for Video Retrieval
Multi-modal learning from video data has seen increased attention recent...
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12/04/2021
Unsupervised Domain Generalization by Learning a Bridge Across Domains
The ability to generalize learned representations across significantly d...
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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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08/23/2021
Dynamic Network Quantization for Efficient Video Inference
Deep convolutional networks have recently achieved great success in vide...
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07/19/2021
Separating Skills and Concepts for Novel Visual Question Answering
Generalization to out-of-distribution data has been a problem for Visual...
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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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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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05/10/2021
Spoken Moments: Learning Joint Audio-Visual Representations from Video Descriptions
When people observe events, they are able to abstract key information an...
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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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03/24/2021
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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12/07/2020
Fine-grained Angular Contrastive Learning with Coarse Labels
Few-shot learning methods offer pre-training techniques optimized for ea...
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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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11/26/2020
Learning from Lexical Perturbations for Consistent Visual Question Answering
Existing Visual Question Answering (VQA) models are often fragile and se...
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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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08/12/2020
We Have So Much In Common: Modeling Semantic Relational Set Abstractions in Videos
Identifying common patterns among events is a key ability in human and m...
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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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07/17/2020
OnlineAugment: Online Data Augmentation with Less Domain Knowledge
Data augmentation is one of the most important tools in training modern ...
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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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06/16/2020
AVLnet: Learning Audio-Visual Language Representations from Instructional Videos
Current methods for learning visually grounded language from videos ofte...
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03/15/2020
