Welcome to V3ALab! (Vision, Ask, Answer, Aact). Artificial Intelligence (AI) currently empowers many tasks in our everyday lives, but there is still a long way to go to create human-level AI. One of the biggest obstacles is how humans can communicate with AI effectively to elicit an appropriate response, whether a textual answer or an action. To this end, our V3ALab aims to develop AI agents that communicates with humans on the basis of visual input, and can complete a sequence of actions in environments. Our V3ALab members mainly work on four research themes that correspond to human basic abilities: vision receives visual information from the environment akin to human perception; ask-answer is the basic communication unit for a human, while the act ability can map to the human’s movement and manipulation abilities. These research themes covers a wide range of tasks and applications including Image Captioning, Visual Question Answering, Referring Expression and Vision-Language Navigation etc.
News
Two papers are accepted by NeurIPS 2021!
- Debiased Visual Question Answering
- Landmark-RxR: Solving Vision-and-Language Navigation with Fine-Grained Alignment Supervision
We are hosting the 2nd REVERIE Challenge on ICCV Workshop 2021!
One paper is accepted by ICCV 2021!
- Know What and Know Where: An Object-and-Room Informed Sequential BERT for Indoor Vision-Language Navigation link
Two papers are accepted by ACM MM 2021!
Three papers are accepted by IJCAI 2021!
We will host the 1st Vision-and-Language Navigation Tutorial, CVPR 2021.
- More details at here
Six papers are accepted by CVPR 2021!
- A Recurrent Vision-and-Language BERT for Navigation
- Jo-SRC: A Contrastive Approach for Combating Noisy Labels
- Sketch, Ground, and Refine: Top-Down Dense Video Captioning
- Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation
- Towards Accurate Text-based Image Captioning with Content Diversity Exploration
- Room-and-Object Aware Knowledge Reasoning for Remote Embodied Referring Expression
One paper is accepted by TMM!
Three papers are accepted by AAAI 2021!
- How to Train Your Agent to Read and Write?
- Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps.
- Confidence-aware Non-repetitive Multimodal Transformers for TextCaps.
Qi Wu will serve as an SPC of IJCAI 2021!
One paper is accepted by NeurIPS!
- Language and Visual Entity Relationship Graph for Agent Navigation
One long paper is accepted by EMNLP Conference Proceeding!
- Sub-Instruction Aware Vision-and-Language Navigation
One paper is accepted by IEEE TPAMI!
- Visual Grounding via Accumulated Attention
Qi Wu will serve as an SPC (Area Chair) of AAAI 2021!
Four papers are accepted by ACM MM 2020!
- Cascade Reasoning Network for Text-based Visual Question Answering
- Visual-Semantic Graph Matching for Visual Grounding
- Give Me Something to Eat: Referring Expression Comprehension with Commonsense Knowledge
- Data-driven Meta-set Based Fine-Grained Visual Classification
Four papers are accepted by ECCV 2020!
- Soft Expert Reward Learning for Vision-and-Language Navigation
- Object-and-Action Aware Model for Visual Language Navigation
- Length Controllable Image Captioning
- Semantic Equivalent Adversarial Data Augmentation for Visual Question Answering
We won the first place in Medical VQA Challenge 2020!
- See Leadboard here
We won the first place in TextVQA Challenge 2020!
- See Leadboard here