Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
ActFusion: a Unified Diffusion Model for Action Segmentation and Anticipation
Authors: Dayoung Gong, Suha Kwak, Minsu Cho
NeurIPS 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results demonstrate the bi-directional benefits between action segmentation and anticipation. Act Fusion achieves the state-of-the-art performance across the standard benchmarks of 50 Salads, Breakfast, and GTEA, outperforming task-specific models in both of the two tasks with a single unified model through joint learning. |
| Researcher Affiliation | Academia | Dayoung Gong Suha Kwak Minsu Cho Pohang University of Science and Technology (POSTECH) EMAIL |
| Pseudocode | Yes | We provide training algorithms of Act Fusion in Alg. 1 and inference algorithms for TAS and LTA in Alg. 2 and Alg. 3, respectively. |
| Open Source Code | Yes | We include the code and instructions for reproduction in the supplementary. The training and validation data is available online. |
| Open Datasets | Yes | We evaluate our method on three widely-used benchmark datasets: 50 Salads [58], Breakfast [36], and GTEA [21] (see Sec. F for details). |
| Dataset Splits | Yes | The dataset is partitioned into 5 splits for cross-validations, and we report the average performance across all splits. |
| Hardware Specification | Yes | All experiments are conducted on a single NVIDIA RTX-3080 GPU. |
| Software Dependencies | No | The paper states, 'We implement Act Fusion using Pytorch [47] and some of the official code repository of Diff Act [43]3 licensed under an MIT License.', but it does not specify the version numbers for Pytorch or any other software libraries used. |
| Experiment Setup | Yes | Table S5 presents the specific hyperparameters used in our experiments for each dataset. |