most citedWhy is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning

14 citations · 20 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2023

Exploring Question Decomposition for Zero-Shot VQA

Zaid Khan, Vijay Kumar BG, Samuel Schulter +2

Visual question answering (VQA) has traditionally been treated as a single-step task where each question receives the same amount of effort, unlike natural human question-answering…

cs.CV20231 cited

Layout Sequence Prediction From Noisy Mobile Modality

Haichao Zhang, Yi Xu, Hongsheng Lu +2

Trajectory prediction plays a vital role in understanding pedestrian movement for applications such as autonomous driving and robotics. Current trajectory prediction models depend…

cs.CV2023

BEV-DG: Cross-Modal Learning under Bird's-Eye View for Domain Generalization of 3D Semantic Segmentation

Miaoyu Li, Yachao Zhang, Xu MA +2

Cross-modal Unsupervised Domain Adaptation (UDA) aims to exploit the complementarity of 2D-3D data to overcome the lack of annotation in a new domain. However, UDA methods rely on…

cs.CV2023

Q: How to Specialize Large Vision-Language Models to Data-Scarce VQA Tasks? A: Self-Train on Unlabeled Images!

Zaid Khan, Vijay Kumar BG, Samuel Schulter +3

Finetuning a large vision language model (VLM) on a target dataset after large scale pretraining is a dominant paradigm in visual question answering (VQA). Datasets for specialized…

cs.CV2023

Uncovering the Missing Pattern: Unified Framework Towards Trajectory Imputation and Prediction

Yi Xu, Armin Bazarjani, Hyung-gun Chi +2

Trajectory prediction is a crucial undertaking in understanding entity movement or human behavior from observed sequences. However, current methods often assume that the observed s…

cs.CV2023

Frame Flexible Network

Yitian Zhang, Yue Bai, Chang Liu +3

Existing video recognition algorithms always conduct different training pipelines for inputs with different frame numbers, which requires repetitive training operations and multipl…