This page shows the most relevant public items for Computer Vision, ranked by trend activity and review signal. Use weekly for fast changes, monthly for more stable patterns, and all-time for evergreen picks.
Book • Dec 5, 2023 • Amazon • Simon J.D. Prince
Grasping the true mechanics of deep learning requires a clear visualization of complex mathematical transformations. This highly visual textbook covers foundational neural networks and visual appli...
Paper • May 11, 2021 • arXiv • Prafulla Dhariwal, Alex Nichol
We show that diffusion models can achieve image sample quality superior to the current state-of-the-art generative models. We achieve this on unconditional image synthesis by finding a better archi...
Paper • May 22, 2017 • arXiv • Joao Carreira, Andrew Zisserman
Video action recognition is a crucial challenge in computer vision, but progress has been hindered by the lack of large-scale, comprehensive datasets comparable to ImageNet. We introduce the Kineti...
Paper • Nov 2, 2017 • arXiv • Aaron van den Oord, Oriol Vinyals, Koray Kavukcuoglu
Learning useful representations without supervision remains a key challenge in machine learning. We propose the Vector Quantised-Variational AutoEncoder (VQ-VAE), a simple yet powerful generative m...
Paper • Feb 26, 2015 • Nature • Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Demis Hassabis
We present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. The model is a convolutional neural networ...
Paper • Feb 28, 2026 • arXiv • Qiang Wang, Xinyuan Gao, SongLin Dong, Jizhou Han, Jiangyang Li, Yuhang He, Yihong Gong
Generating highly detailed, temporally accurate video captions requires models to understand complex spatial and temporal dynamics. VDC-Agent introduces an autonomous framework where the captioning...
Paper • Jan 22, 2026 • arXiv • John Smith, Alice Chen, Wei Lin
Traditional autonomous web agents rely heavily on parsing underlying website code which often breaks during dynamic updates. We propose a purely visual framework that navigates user interfaces acro...
Paper • Feb 22, 2026 • arXiv • Tatsunori Hashimoto, Percy Liang, Xinyi Wang
Current web agents rely heavily on underlying HTML DOM structures, making them brittle to website updates and entirely incapable of navigating dynamic, canvas-based, or non-web applications. We pro...
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