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20212023
most citedMake-A-Video: Text-to-Video Generation without Text-Video Data

315 citations · 665 across the 16 of their papers we have counts for

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12 papers · 1 filter

cs.CV2023★ 1 cited

Context Perception Parallel Decoder for Scene Text Recognition

Yongkun Du, Zhineng Chen, Caiyan Jia +4

Scene text recognition (STR) methods have struggled to attain high accuracy and fast inference speed. Autoregressive (AR)-based models implement the recognition in a character-by-c…

cs.CV2023★ 4 cited

Towards Anytime Optical Flow Estimation with Event Cameras

Yaozu Ye, Hao Shi, Kailun Yang +5

Event cameras respond to changes in log-brightness at the millisecond level, making them ideal for optical flow estimation. However, existing datasets from event cameras provide on…

cs.CV2023★ 27 cited

Latent-Shift: Latent Diffusion with Temporal Shift for Efficient Text-to-Video Generation

Jie An, Songyang Zhang, Harry Yang +4

We propose Latent-Shift -- an efficient text-to-video generation method based on a pretrained text-to-image generation model that consists of an autoencoder and a U-Net diffusion m…

cs.CV2022★ 153 cited

SpaText: Spatio-Textual Representation for Controllable Image Generation

Omri Avrahami, Thomas Hayes, Oran Gafni +6

Recent text-to-image diffusion models are able to generate convincing results of unprecedented quality. However, it is nearly impossible to control the shapes of different regions/…

cs.CV2022★ 1 cited

Beyond the Field-of-View: Enhancing Scene Visibility and Perception with Clip-Recurrent Transformer

Hao Shi, Qi Jiang, Kailun Yang +3

Vision sensors are widely applied in vehicles, robots, and roadside infrastructure. However, due to limitations in hardware cost and system size, camera Field-of-View (FoV) is ofte…

cs.CV2022★ 315 cited

Make-A-Video: Text-to-Video Generation without Text-Video Data

Uriel Singer, Adam Polyak, Thomas Hayes +10

We propose Make-A-Video -- an approach for directly translating the tremendous recent progress in Text-to-Image (T2I) generation to Text-to-Video (T2V). Our intuition is simple: le…

cs.CV2022★ 70 cited

PP-OCRv3: More Attempts for the Improvement of Ultra Lightweight OCR System

Chenxia Li, Weiwei Liu, Ruoyu Guo +9

Optical character recognition (OCR) technology has been widely used in various scenes, as shown in Figure 1. Designing a practical OCR system is still a meaningful but challenging…

cs.CV2022★ 26 cited

SVTR: Scene Text Recognition with a Single Visual Model

Yongkun Du, Zhineng Chen, Caiyan Jia +5

Dominant scene text recognition models commonly contain two building blocks, a visual model for feature extraction and a sequence model for text transcription. This hybrid architec…

cs.CV2022

MUGEN: A Playground for Video-Audio-Text Multimodal Understanding and GENeration

Thomas Hayes, Songyang Zhang, Xi Yin +6

Multimodal video-audio-text understanding and generation can benefit from datasets that are narrow but rich. The narrowness allows bite-sized challenges that the research community…

cs.CV2022★ 2 cited

Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformer

Songwei Ge, Thomas Hayes, Harry Yang +5

Videos are created to express emotion, exchange information, and share experiences. Video synthesis has intrigued researchers for a long time. Despite the rapid progress driven by…

cs.CV2022

PanoFlow: Learning 360° Optical Flow for Surrounding Temporal Understanding

Hao Shi, Yifan Zhou, Kailun Yang +7

Optical flow estimation is a basic task in self-driving and robotics systems, which enables to temporally interpret traffic scenes. Autonomous vehicles clearly benefit from the ult…

cs.CV2021

DCF-ASN: Coarse-to-fine Real-time Visual Tracking via Discriminative Correlation Filter and Attentional Siamese Network

Xizhe Xue, Ying Li, Xiaoyue Yin +1

Discriminative correlation filters (DCF) and siamese networks have achieved promising performance on visual tracking tasks thanks to their superior computational efficiency and rel…