https://github.com/facebookresearch/mmf/tree/main/projects/unit
공식 코드UniT: Multimodal Multitask Learning with a Unified Transformer
Papers with Code 아카이브
16k
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 6
- 평가표
- 1
- 보존된 평가 기록
- 1
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/facebookresearch/mvit
공식 코드MViTv2: Improved Multiscale Vision Transformers for Classification and Detection
https://github.com/facebookresearch/nerf-det
공식 코드NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object Detection
https://github.com/facebookresearch/omni3d
공식 코드Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild
https://github.com/facebookresearch/projectaria_tools
공식 코드Aria Digital Twin: A New Benchmark Dataset for Egocentric 3D Machine Perception
https://github.com/facebookresearch/r-mae
공식 코드https://github.com/facebookresearch/self_defeating_improvements
공식 코드Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems
https://github.com/facebookresearch/sylph-few-shot-detection
공식 코드Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detection
https://github.com/facebookresearch/unbiased-teacher
공식 코드https://github.com/facebookresearch/unbiased-teacher-v2
공식 코드Unbiased Teacher v2: Semi-supervised Object Detection for Anchor-free and Anchor-based Detectors
https://github.com/facebookresearch/video-nonlocal-net
공식 코드https://github.com/facebookresearch/vlpart
공식 코드https://github.com/facebookresearch/votenet
공식 코드https://github.com/facebookresearch/xcit
공식 코드https://github.com/facias914/A-Simple-Detector-is-a-Strong-Tracker
공식 코드https://github.com/facias914/sood-mcl
공식 코드https://github.com/fahadshamshad/awesome-transformers-in-medical-imaging
공식 코드https://github.com/falsr/FALSR
공식 코드Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search
https://github.com/fanamber831/sgglc-net
공식 코드Semantic-Guided Global-Local Collaborative Networks for Lightweight Image Super-Resolution
https://github.com/fanghua-yu/osrt
공식 코드OSRT: Omnidirectional Image Super-Resolution with Distortion-aware Transformer
https://github.com/fangyanwen1106/RLANet
공식 코드Recurrence along Depth: Deep Convolutional Neural Networks with Recurrent Layer Aggregation
https://github.com/fangyi-chen/sqr
공식 코드Enhanced Training of Query-Based Object Detection via Selective Query Recollection
https://github.com/fanq15/FewX
공식 코드Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector
https://github.com/fanq15/GCoNet
공식 코드Group Collaborative Learning for Co-Salient Object Detection
https://github.com/fanyang587/MGL
공식 코드https://github.com/fanyihua0309/friendnet
공식 코드https://github.com/faridghm/meta-sel
공식 코드3D-model ShapeNet Core Classification using Meta-Semantic Learning
https://github.com/fasterdecoding/snapkv
공식 코드SnapKV: LLM Knows What You are Looking for Before Generation
https://github.com/fatemehshiri/spatial-mm
공식 코드An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
https://github.com/fawazsammani/look-and-modify
공식 코드https://github.com/fcakyon/sahi-benchmark
공식 코드Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection
https://github.com/fcdl94/RobotChallenge
공식 코드The RGB-D Triathlon: Towards Agile Visual Toolboxes for Robots
https://github.com/fcdl94/mma
공식 코드Modeling Missing Annotations for Incremental Learning in Object Detection
https://github.com/fcendra/sl3d
공식 코드https://github.com/fcjian/AeDet
공식 코드https://github.com/fcjian/TOOD
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.