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Found 6 papers, 2 papers with code
Text2Scene: Text-driven Indoor Scene Stylization with Part-aware Details
We propose Text2Scene, a method to automatically create realistic textures for virtual scenes composed of multiple objects.
Learning Geometry-aware Representations by Sketching
Our method, coined Learning by Sketching (LBS), learns to convert an image into a set of colored strokes that explicitly incorporate the geometric information of the scene in a single inference step without requiring a sketch dataset.
SelecMix: Debiased Learning by Contradicting-pair Sampling
Experiments on standard benchmarks demonstrate the effectiveness of the method, in particular when label noise complicates the identification of bias-conflicting examples.
On the Importance of Critical Period in Multi-stage Reinforcement Learning
The initial years of an infant's life are known as the critical period, during which the overall development of learning performance is significantly impacted due to neural plasticity.
Ev-NeRF: Event Based Neural Radiance Field
We present Ev-NeRF, a Neural Radiance Field derived from event data.
Ev-TTA: Test-Time Adaptation for Event-Based Object Recognition
We introduce Ev-TTA, a simple, effective test-time adaptation algorithm for event-based object recognition.
Ranked #1 on
Robust classification
on N-ImageNet
