Projects sharing features with Cinemo

This project is a computer vision benchmark and image classification dataset used to measure and compare the accuracy of machine learning models. It provides a standardized collection of labeled fashion product images and training data formatted to be compatible with the MNIST dataset structure. The dataset consists of fixed-dimension grayscale images and label-based category mappings, stored in a binary format. It includes pre-split training and testing sets and a static distribution to ensure consistent cross-model benchmarking. The repository supports image classification benchmarking and

CVPR2018 - pixel embedding & grouping for structured prediction, e.g., instance segmentation

Code for the ECCV 2018 paper "Pairwise Confusion for Fine-Grained Visual Classification"

CVPR'25Tora: Trajectory-oriented Diffusion Transformer for Video Generation

Contains implementation of Guided Attention Inference Network (GAIN) presented in Tell Me Where to Look(CVPR 2018). This repository aims to apply GAIN on fcn8 architecture used for segmentation.

Official implementation of GANimation. In this work we introduce a novel GAN conditioning scheme based on Action Units (AU) annotations, which describe in a continuous manifold the anatomical facial movements defining a human expression. Our approach permits controlling the magnitude of…

This repository contains the TensorFlow code for our NeurIPS 2018 paper “Unsupervised Attention-guided Image-to-Image Translation”. This code is based on the TensorFlow implementation of CycleGAN provided by Harry Yang. You may need to train several times as the quality of the results are…

CVPR2018: Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatio-temporal Patterns

3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This work is based on our ECCV'18 paper, 3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation.

CVPR'18 ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image

Code for PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning

Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

"Zero-Shot" Super-Resolution using Deep Internal Learning

Multi-Content GAN for Few-Shot Font Style Transfer at CVPR 2018

Code for our CVPR 2018 paper: "Synthesizing Images of Humans in Unseen Poses"

记录每天整理的计算机视觉/深度学习/机器学习相关方向的论文