Video Large Language Models (VLLMs) unlock world-knowledge-aware video understanding through pretraining on internet-scale data and have already shown promise o...
The application of Machine Learning (ML) to the diagnosis of rare diseases, such as collagen VI-related dystrophies (COL6-RD), is fundamentally limited by the s...
Existing video generation models struggle to maintain long-term spatial and temporal consistency due to the dense, high-dimensional nature of video signals. To ...
At the most basic level, pixels are the source of the visual information through which we perceive the world. Pixels contain information at all levels, ranging ...
In recent multimodal research, the diffusion paradigm has emerged as a promising alternative to the autoregressive paradigm (AR), owing to its unique decoding a...
We present Gaussian Pixel Codec Avatars (GPiCA), photorealistic head avatars that can be generated from multi-view images and efficiently rendered on mobile dev...
Foundation models are vital tools in various Computer Vision applications. They take as input a single RGB image and output a deep feature representation that i...
Active Speaker Detection (ASD) aims to identify who is currently speaking in each frame of a video. Most state-of-the-art approaches rely on late fusion to comb...
Autoregressive video diffusion models hold promise for world simulation but are vulnerable to exposure bias arising from the train-test mismatch. While recent w...
Evaluations of image compression performance which include human preferences have generally found that naive distortion functions such as MSE are insufficiently...
The misuse of AI-driven video generation technologies has raised serious social concerns, highlighting the urgent need for reliable AI-generated video detectors...
Prevailing Vision-Language-Action Models (VLAs) for robotic manipulation are built upon vision-language backbones pretrained on large-scale, but disconnected st...
This paper proposes a training data augmentation pipeline that combines synthetic image data with neural style transfer in order to address the vulnerability of...
The computational and memory overheads associated with expanding the context window of LLMs severely limit their scalability. A noteworthy solution is vision-te...
Working memory enables the brain to integrate transient information for rapid decision-making. Artificial networks typically replicate this via recurrent or par...
Edit your config.toml while the app is running and watch the pipeline update instantly. No recompiling. No stopping the camera. Pure iteration bliss. Why This M...
Introduction Data annotation is a foundational process in artificial intelligence that enables machines to learn from real‑world data. It involves adding meani...
An AI background remover may feel like magic at first glance. You upload an image, click a button, and the background disappears. Behind that simple interaction...
Renderizado de vídeo de cámara con Metal sin AVCaptureVideoPreviewLayer En este tutorial vamos a renderizar el video de la cámara directamente en pantalla usan...
The core challenge for streaming video generation is maintaining the content consistency in long context, which poses high requirement for the memory design. Mo...
This paper does not introduce a novel method but instead establishes a straightforward, incremental, yet essential baseline for video temporal grounding (VTG), ...
Non-parametric quantization has received much attention due to its efficiency on parameters and scalability to a large codebook. In this paper, we present a uni...
We introduce CRISP, a method that recovers simulatable human motion and scene geometry from monocular video. Prior work on joint human-scene reconstruction reli...
Recent advancements in 3D generative modeling have significantly improved the generation realism, yet the field is still hampered by existing representations, w...
