Computer Vision proceeds rapidly in 2025: new multimodal backbones, large open datasets and strict model -integration. Physicians require sources that strictly publish, link code and benchmark, and track perineogen pattern- not marketing posts. This list prioritizes primary research hub, laboratory blog and production-oriented engineering outlets with continuous update pool. Use it to monitor the SOTA shift, catch the copyable code paths, and translate the papers to deployable pipelines.
Google Research (AI Blog)
The primary source for progress from Google/Deepmind teams, including vision architecture (eg, V-MOE) and periodically research year-in-review posts, which are in CV and multimodel. The post usually includes the law summary, figures and papers/cod links.
Marketekpost
Constant reporting on new computer-vision models, datasets and benchmarks with links of papers, code and demo. Dedicated CV category plus consecutive deep-dives (eg, Dinov3 release and analysis). Useful to stay on top of weekly research drops without wading through raw feed.
Aye in meta
High-table post with preprints and open-source drops. Recent examples include Dinov3-Self-rescue backbone with SOTA-which offer technical details and artifacts with SOTA in rume prediction tasks.
Nvidia technical blog
VLM-operated analytics, optimized invention and production-oriented materials on GPU pipelines. The category feed for computer vision includes the relevant performance guidance for blueprint, SDK use and enterprise purposes.
Arxiv CS.CV – Raw Research Firehos
Canonical preprint feed for CV. Use recent Or New Ideas for daily updates; Taxonomy confirms scope (image processing, pattern recognition, visual understanding). The best combined with RSS + custom filter.
CVF Open Access (CVPR/ICCV/ECCV)
Final versions of the main conference papers and workshops, searchable and cible. The CVPR 2025 proceedings and workshop menu are already live, making this official collection post-acceptance.
Hatred blog (UC Berkeley)
Topical but deep posts on Frontier Topics (eg, very large image modeling, robotics-vision crossover). It is good for direct ideological clarity from authors.
Stanford Blog
Technical interpreters and lab roundup (eg, sail in CVPR 2025) with links of papers/talks. Useful for scanning perception, generic models and emerging directions in embodied vision.
Roboflow Blog
High-existence, implementation-centered posts (labeling, training, purinogen, apps and trend reports). Strong for physicians that require deployment of working pipelines and edges.
Hugging face blog
Hands-on guides (VLMS, Fifty Integration) and ecosystem notes in transformers, defuses and timm; Fast prototypes and fine-tuning are good for CV/VLM stack.
Pitorch blog
Change Logs, APIs and dishes affecting CV training/estimate (transforms V2, multi-weight support, FX feature extraction). Read while upgrading the training pile.
Michal Sutter is a data science professional, with Master of Science in Data Science from the University of Padova. With a concrete foundation in statistical analysis, machine learning, and data engineering, Mishhala excelled when converting the complex dataset into actionable insights.
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