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20162023
most citedBeyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking

1.8k citations · 1.9k across the 12 of their papers we have counts for

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11 papers · 1 filter

cs.CV2023

StyleGenes: Discrete and Efficient Latent Distributions for GANs

Evangelos Ntavelis, Mohamad Shahbazi, Iason Kastanis +3

We propose a discrete latent distribution for Generative Adversarial Networks (GANs). Instead of drawing latent vectors from a continuous prior, we sample from a finite set of lear…

cs.CV2023

Mask-Free Video Instance Segmentation

Lei Ke, Martin Danelljan, Henghui Ding +3

The recent advancement in Video Instance Segmentation (VIS) has largely been driven by the use of deeper and increasingly data-hungry transformer-based models. However, video masks…

cs.CV2022

ManiFlow: Implicitly Representing Manifolds with Normalizing Flows

Janis Postels, Martin Danelljan, Luc Van Gool +1

Normalizing Flows (NFs) are flexible explicit generative models that have been shown to accurately model complex real-world data distributions. However, their invertibility constra…

cs.CV202210 cited

AVisT: A Benchmark for Visual Object Tracking in Adverse Visibility

Mubashir Noman, Wafa Al Ghallabi, Daniya Najiha +7

One of the key factors behind the recent success in visual tracking is the availability of dedicated benchmarks. While being greatly benefiting to the tracking research, existing b…

cs.CV2022

Video Mask Transfiner for High-Quality Video Instance Segmentation

Lei Ke, Henghui Ding, Martin Danelljan +3

While Video Instance Segmentation (VIS) has seen rapid progress, current approaches struggle to predict high-quality masks with accurate boundary details. Moreover, the predicted s…

cs.CV2022

Tracking Every Thing in the Wild

Siyuan Li, Martin Danelljan, Henghui Ding +2

Current multi-category Multiple Object Tracking (MOT) metrics use class labels to group tracking results for per-class evaluation. Similarly, MOT methods typically only associate o…