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Visual AI

CycleGAN Unpaired Translation

CycleGAN learns to translate images between two visual domains (like horses to zebras, or photos to paintings) without ever needing matched before-and-after…

2 min readRead
Visual AI

SPADE Semantic Image Synthesis

SPADE (Spatially-Adaptive Normalization) turns a simple labeled layout, like a child's coloring-book map of 'sky here, grass there, tree here'…

2 min readRead
Visual AI

DragGAN Interactive Editing

DragGAN lets you edit an image by literally dragging points: grab a spot and drag it to a target, and the picture deforms realistically, changing pose…

2 min readRead
Visual AI

Diffusion Transformers

Diffusion Transformers (DiTs) swap the convolutional U-Net at the heart of image and video generators for a Transformer backbone.

2 min readRead
Visual AI

Feature Pyramid Networks

Feature Pyramid Networks (FPN) let detectors spot objects at wildly different sizes by building a multi-scale 'pyramid' of features cheaply.

2 min readRead
Visual AI

Non-Maximum Suppression

Non-Maximum Suppression (NMS) is the cleanup step that turns a messy pile of overlapping detection boxes into one tidy box per object.

2 min readRead
Visual AI

Spatial Transformer Networks

Spatial Transformer Networks (STNs) are learnable modules that let a neural network actively warp, rotate, crop, or rescale its input to focus on what…

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Visual AI

Stereo Depth Estimation

Stereo depth estimation recovers how far away things are by comparing two slightly offset camera views, just like your two eyes do.

2 min readRead
Visual AI

Point Cloud Processing

A point cloud is a set of 3D points (X, Y, Z) that captures the shape of real objects and spaces, often from LiDAR or depth sensors.

2 min readRead
Visual AI

Signed Distance Functions

A signed distance function (SDF) describes a 3D shape by telling you, for any point in space, how far it is to the nearest surface, with a sign that says…

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Visual AI

Deformable Convolutions

Deformable convolutions let a neural network bend its sampling grid to follow the actual shape of objects instead of forcing it through a rigid square window.

2 min readRead
Visual AI

DINO Self-Distillation

DINO is a self-supervised method that trains a vision transformer to understand images with no labels at all, by having the network teach itself.

2 min readRead

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