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3dblender

acsm

Project Repo for Articulation Aware CSM

adversarial-inverse-graphics-networks-for-faces

alignprop

AlignProp uses direct reward backpropogation for the alignment of large-scale text-to-image diffusion models. Our method is 25x more sample and compute efficient than reinforcement learning methods (PPO) for finetuning Stable Diffusion

artminer

(CVPR2019)Pytorch implementation of Paper "Discovering Visual Patterns in Art Collections with Spatially-consistent Feature Learning"

association-net

This is an unofficial implementation of the Paper "Learning Feature Hierarchies from Long-Range Temporal Associations in Videos" By Panna Felsen, Katerina Fragkiadaki, Jitendra Malik, Alexei Efros

blender_emblang

blender_shapenet_render

Blender render script for ShapeNet models

blockchain_voting

cementapp

App made on android studio for predicting clinker cost using Input resources

cmu-vision.github.io

complexautoencoder

Code for the paper: Complex-Valued Autoencoders for Object Discovery

continuous-control

Udacity deep reinforcement learning continuous control project

continuous-control-using-policy-based-rl-method

convhypernetcomp

convhypernetcomp_xav

convolutional_occupancy_networks

[ECCV'20] Convolutional Occupancy Networks

cs224d

Code for Stanford CS224D: deep learning for natural language understanding

dalle-pytorch

Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

darknet

Convolutional Neural Networks

data_clevr_ashar_account

deep-reinforcement-learning

Repo for the Deep Reinforcement Learning Nanodegree program

depth-adaptive-visual-tracking-tf

This is an unofficial implementation of the Paper "Depth-Adaptive Computational Policies for Efficient Visual Tracking" By Chris Ying, Katerina Fragkiadaki

detic

Code release for "Detecting Twenty-thousand Classes using Image-level Supervision".

diffusion-tta

Diffusion-TTA improves pre-trained discriminative models such as image classifiers or segmentors using pre-trained generative models.

dino

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

disentangling-3d-prototypical-nets

We present neural architectures that disentangle RGB-D images into objects' shapes and styles and a map of the background scene, and explore their applications for few-shot 3D object detection and few-shot concept classification.

diskread_benchmark

dit

emblang

Embodied Language Grounding With 3D Visual Feature Representations