A PyTorch implementation of VL-JEPA from the paper "VL-JEPA: Joint Embedding Predictive Architecture for Vision-language" (arXiv:2512.10942v2). vl-jepa/ ├── src/ │ ├── model.py # Core VL-JEPA model ...
How can you protect the sanctity of a raw photograph from AI interference when it’s already been automatically run through AI inside the camera? New research seeks to restore ‘true’ sensor data – also ...
In addition to the financial burdens of HEVC licensing, the risk of lawsuits from patent holders can deter companies from ...
Back in January 2024, Firefly released the CT36L AI smart security cameras, built around the Rockchip RV1106G2 SoC with a 0.5 ...
Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
Abstract: To alleviate the expensive human labeling problem, semi-supervised semantic segmentation utilizes a few labeled images along with an abundance of unlabeled images to predict the pixel-level ...
This paper presents the design and FPGA implementation of a high-throughput BCH (n,k) encoder and decoder using a fully pipelined architecture. Unlike conventional designs based on finite state ...
UniScene3D learns transferable 3D scene representations from multi-view colored pointmaps, unifying RGB appearance and world-aligned geometry within a single ViT encoder. We evaluate its effectiveness ...
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