sangnekim

sangnekim's Stars

• benhenryL/Deblurring-3D-Gaussian-Splatting

  Language:Python2419

• stnamjef/MipGrid

  Language:Python16

• benhenryL/SharpNeRF

  Language:Python301

• alxndrTL/mamba.py

  A simple and efficient Mamba implementation in pure PyTorch and MLX.

  Language:Python90382

• extremebird/Hydra

  Language:Python192

• hila-chefer/Transformer-Explainability

  [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

  Language:Jupyter Notebook1.8k234

• dongzelian/SSF

  [NeurIPS'22] This is an official implementation for "Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning".

  Language:Python16312

• luogen1996/RepAdapter

  Official implementation of "Towards Efficient Visual Adaption via Structural Re-parameterization".

  Language:Python19223

• artidoro/qlora

  QLoRA: Efficient Finetuning of Quantized LLMs

  Language:Jupyter Notebook9.9k816

• microsoft/LoRA

  Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

  Language:Python10.3k661

• 52CV/CVPR-2023-Papers

  92079

• ShoufaChen/AdaptFormer

  [NeurIPS 2022] Implementation of "AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition"

  Language:Python31717

• JierunChen/FasterNet

  [CVPR 2023] Code for PConv and FasterNet

  Language:Python67255

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook46.7k5.5k

• sangnekim/SMPConv

  [CVPR2023] "SMPConv: Self-moving Point Representations for Continuous Convolution"

  Language:HTML522

• DingXiaoH/RepLKNet-pytorch

  Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs (CVPR 2022)

  Language:Python85986

• minjung-s/BallGAN

  [ICCV23] BallGAN: 3D-aware Image Synthesis with a Spherical Background

  Language:Python381

• daniel03c1/masked_wavelet_nerf

  Language:Python785

• stnamjef/SPINN

  Source code for Separable PINN

  Language:Python4818

• eric-ai-lab/PEViT

  Official implementation of AAAI 2023 paper "Parameter-efficient Model Adaptation for Vision Transformers"

  Language:Python945

• LuChengTHU/dpm-solver

  Official code for "DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps" (Neurips 2022 Oral)

  Language:Python1.5k118

• ilovemyminutes/CLIK

  Jihyeong Ko et al., Contrastive Learning for Topic-Dependent Image Ranking, 2022

  Language:Python1

• kzl/decision-transformer

  Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

  Language:Python2.3k440

• montrealrobotics/iv_rl

  IV-RL - Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation

  Language:Python354

• jwcho5576/streamable_nf

  Source code of "Streamable Neural Fields"

  Language:Python372

• rjbruin/flexconv

  Code repository for the ICLR 2022 paper "FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes" https://openreview.net/forum?id=3jooF27-0Wy

  Language:Python1158

• VITA-Group/SLaK

  [ICLR 2023] "More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity"; [ICML 2023] "Are Large Kernels Better Teachers than Transformers for ConvNets?"

  Language:HTML26222

• hancyran/RepSurf

  [CVPR 2022 Oral] Official implementation for "Surface Representation for Point Clouds"

  Language:Python33025

• guochengqian/PointNeXt

  [NeurIPS'22] PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies

  Language:Shell757108

• facebookresearch/ConvNeXt

  Code release for ConvNeXt model

  Language:Python5.7k692