Papers with Code · CC BY-SA 4.0

Breakfast

아카이브 평가 37건 · 마지막 적재/변경 2026-10-30

평가 기록

과거 수집 기록이며 최신 순위가 아닙니다. 데이터셋 버전·split·실험 조건과 지표 방향이 검증되지 않은 결과는 직접 비교할 수 없습니다. 날짜는 논문 날짜이며 최신 평가일을 뜻하지 않습니다.

표가 화면보다 넓으면 좌우로 스크롤하여 논문과 구현 링크를 확인하세요.

원본 기록 순서 · 순위 미부여
모델	원본 지표·값	논문	구현
AdaFocus (newly extracted I3D-features, LT-Context model)	F1@10% 82.1 F1@50% 67.5 Acc 78.0 Edit 78.3 F1@25% 79.0 Average F1 76.2	Towards Weakly Supervised End-to-end Learning for Long-video Action Recognition 2023-11-28	연결 없음
FACT (efficient hybrid of convolution and transformer model)	F1@10% 81.4 F1@50% 66.2 Acc 76.2 Edit 79.7 F1@25% 76.5 Average F1 74.7	FACT: Frame-Action Cross-Attention Temporal Modeling for Efficient Action Segmentation 2024-01-01	코드 1
ASQuery	F1@10% 80.7 F1@50% 66.5 Acc 77.9 Edit 78.4 F1@25% 76.5 Average F1 74.6	ASQuery: A Query-based Model for Action Segmentation 2024-09-30	코드 1
BIT	F1@10% 80.6 F1@50% 64.7 Acc 75.5 Edit 79.0 F1@25% 75.8 Average F1 73.7	BIT: Bi-Level Temporal Modeling for Efficient Supervised Action Segmentation 2023-08-28	연결 없음
DiffAct	F1@10% 80.3 F1@50% 64.6 Acc 76.4 Edit 78.4 F1@25% 75.9 Average F1 73.6	Diffusion Action Segmentation 2023-03-31	코드 1
BaFormer	F1@10% 79.2 F1@50% 63.2 Acc 76.6 Edit 77.3 F1@25% 74.9 Average F1 72.4	Efficient Temporal Action Segmentation via Boundary-aware Query Voting 2024-05-25	코드 1
CETNet	F1@10% 79.3 F1@50% 61.9 Acc 74.9 Edit 77.8 F1@25% 74.3 Average F1 71.8	Cross-Enhancement Transformer for Action Segmentation 2022-05-19	코드 1
SF-TMN(ASFormer)	F1@10% 78.7 F1@50% 62.2 Acc 77.0 Edit 77.0 F1@25% 74.0 Average F1 71.6	SF-TMN: SlowFast Temporal Modeling Network for Surgical Phase Recognition 2023-06-15	연결 없음
ASPnet	F1@10% 78.1 F1@50% 60.8 Acc 75.9 Edit 76.3 F1@25% 72.9 Average F1 70.6	ASPnet: Action Segmentation With Shared-Private Representation of Multiple Data Sources 2023-01-01	연결 없음
LTContext	F1@10% 77.6 F1@50% 60.1 Acc 74.2 Edit 77.0 F1@25% 72.6 Average F1 70.1	How Much Temporal Long-Term Context is Needed for Action Segmentation? 2023-08-22	코드 1
EUT	F1@10% 76.2 F1@50% 59.8 Acc 75 Edit 74.6 F1@25% 71.8 Average F1 69.3	Do we really need temporal convolutions in action segmentation? 2022-05-26	코드 1
UVAST	F1@10% 76.9 F1@50% 58 Acc 69.7 Edit 77.1 F1@25% 71.5 Average F1 68.8	Unified Fully and Timestamp Supervised Temporal Action Segmentation via Sequence to Sequence Translation 2022-09-01	코드 1 · 코드 2
ASFormer	F1@10% 76.0 F1@50% 57.4 Acc 73.5 Edit 75.0 F1@25% 70.6 Average F1 68.0	ASFormer: Transformer for Action Segmentation 2021-10-16	코드 1
DPRN	F1@10% 75.6 F1@50% 57.6 Acc 71.7 Edit 75.1 F1@25% 70.5 Average F1 67.9	Maximization and restoration: Action segmentation through dilation passing and temporal reconstruction 2022-05-02	연결 없음
ASRF + HASR	F1@10% 74.7 F1@50% 57.0 Acc 69.4 Edit 71.9 F1@25% 69.5 Average F1 67.1	Refining Action Segmentation With Hierarchical Video Representations 2021-01-01	코드 1
G2L(SSTDA)	F1@10% 76.3 F1@50% 54.6 Acc 70.8 Edit 74.5 F1@25% 69.9 Average F1 66.9	Global2Local: Efficient Structure Search for Video Action Segmentation 2021-01-04	코드 1 · 코드 2
FIFA + MS-TCN	F1@10% 75.5 F1@50% 54.8 Acc 68.6 Edit 78.5 F1@25% 70.2 Average F1 66.8	FIFA: Fast Inference Approximation for Action Segmentation 2021-08-09	연결 없음
DA	F1@10% 74.2 F1@50% 56.5 Acc 71.0 Edit 73.6 F1@25% 68.6 Average F1 66.4	Action Segmentation with Mixed Temporal Domain Adaptation 2021-04-15	연결 없음
ETSN	F1@10% 74.0 F1@50% 56.2 Acc 67.8 Edit 70.3 F1@25% 69.0 Average F1 66.4	Efficient Two-Step Networks for Temporal Action Segmentation 2021-04-30	코드 1
ASRF	F1@10% 74.3 F1@50% 56.1 Acc 67.6 Edit 72.4 F1@25% 68.9 Average F1 66.4	Alleviating Over-segmentation Errors by Detecting Action Boundaries 2020-07-14	코드 1
SSTDA	F1@10% 75.0 F1@50% 55.2 Acc 70.2 Edit 73.7 F1@25% 69.1 Average F1 66.4	Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation 2020-03-05	코드 1
C2F-TCN	F1@10% 72.2 F1@50% 57.6 Acc 76.0 Edit 69.6 F1@25% 68.7 Average F1 66.2	Coarse to Fine Multi-Resolution Temporal Convolutional Network 2021-05-23	코드 1
BCN	F1@10% 68.7 F1@50% 55.0 Acc 70.4 Edit 66.2 F1@25% 65.5 Average F1 63.1	Boundary-Aware Cascade Networks for Temporal Action Segmentation 논문 날짜 미기재	코드 1
MuCon	F1@10% 73.2 F1@50% 48.4 Acc 62.8 Edit 76.3 F1@25% 66.1 Average F1 62.6	Fast Weakly Supervised Action Segmentation Using Mutual Consistency 2019-04-05	코드 1
DS-TCN	F1@10% 67.70 F1@50% 49.18 Acc 70.75 Edit 69.02 F1@25% 62.05 Average F1 59.6	Depthwise Separable Temporal Convolutional Network for Action Segmentation 2021-01-19	연결 없음
DTGRM	F1@10% 68.7 F1@50% 46.6 Acc 68.3 Edit 68.9 F1@25% 61.9 Average F1 59.1	Temporal Relational Modeling with Self-Supervision for Action Segmentation 2020-12-14	코드 1
MS-TCN++ (I3D)	F1@10% 64.1 F1@50% 45.9 Acc 67.6 Edit 65.6 F1@25% 58.6 Average F1 56.2	MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation 2020-06-16	코드 1
MS-TCN++(I3D) (sh)	F1@10% 63.3 F1@50% 44.5 Acc 67.3 Edit 64.9 F1@25% 57.7 Average F1 55.2	MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation 2020-06-16	코드 1
GTRM	F1@10% 57.5 F1@50% 43.3 Acc 65.0 Edit 58.7 F1@25% 54.0 Average F1 51.6	Improving Action Segmentation via Graph-Based Temporal Reasoning 2020-06-01	연결 없음
MS-TCN (IDT)	F1@10% 58.2 F1@50% 40.8 Acc 65.1 Edit 61.4 F1@25% 52.9 Average F1 50.6	MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation 2019-03-05	코드 1 · 코드 2