298 citations · 322 across the 11 of their papers we have counts for
11 papers
ExoViP: Step-by-step Verification and Exploration with Exoskeleton Modules for Compositional Visual Reasoning
Yuxuan Wang, Alan Yuille, Zhuowan Li +1
Compositional visual reasoning methods, which translate a complex query into a structured composition of feasible visual tasks, have exhibited a strong potential in complicated mul…
Causal-CoG: A Causal-Effect Look at Context Generation for Boosting Multi-modal Language Models
Shitian Zhao, Zhuowan Li, Yadong Lu +2
While Multi-modal Language Models (MLMs) demonstrate impressive multimodal ability, they still struggle on providing factual and precise responses for tasks like visual question an…
3D-Aware Visual Question Answering about Parts, Poses and Occlusions
Xingrui Wang, Wufei Ma, Zhuowan Li +2
Despite rapid progress in Visual question answering (VQA), existing datasets and models mainly focus on testing reasoning in 2D. However, it is important that VQA models also under…
Convolution-enhanced Evolving Attention Networks
Yujing Wang, Yaming Yang, Zhuo Li +7
Attention-based neural networks, such as Transformers, have become ubiquitous in numerous applications, including computer vision, natural language processing, and time-series anal…
Localization vs. Semantics: Visual Representations in Unimodal and Multimodal Models
Zhuowan Li, Cihang Xie, Benjamin Van Durme +1
Despite the impressive advancements achieved through vision-and-language pretraining, it remains unclear whether this joint learning paradigm can help understand each individual mo…
Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoning
Zhuowan Li, Xingrui Wang, Elias Stengel-Eskin +4
Visual Question Answering (VQA) models often perform poorly on out-of-distribution data and struggle on domain generalization. Due to the multi-modal nature of this task, multiple…
Visual Commonsense in Pretrained Unimodal and Multimodal Models
Chenyu Zhang, Benjamin Van Durme, Zhuowan Li +1
Our commonsense knowledge about objects includes their typical visual attributes; we know that bananas are typically yellow or green, and not purple. Text and image corpora, being…
SwapMix: Diagnosing and Regularizing the Over-Reliance on Visual Context in Visual Question Answering
Vipul Gupta, Zhuowan Li, Adam Kortylewski +3
While Visual Question Answering (VQA) has progressed rapidly, previous works raise concerns about robustness of current VQA models. In this work, we study the robustness of VQA mod…
Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images
Zhuowan Li, Elias Stengel-Eskin, Yixiao Zhang +4
While neural symbolic methods demonstrate impressive performance in visual question answering on synthetic images, their performance suffers on real images. We identify that the lo…
Context-Aware Group Captioning via Self-Attention and Contrastive Features
Zhuowan Li, Quan Tran, Long Mai +2
While image captioning has progressed rapidly, existing works focus mainly on describing single images. In this paper, we introduce a new task, context-aware group captioning, whic…
FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification
Yixiao Ge, Zhuowan Li, Haiyu Zhao +4
Person re-identification (reID) is an important task that requires to retrieve a person's images from an image dataset, given one image of the person of interest. For learning robu…