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Research, evidence gathering, literature, reports, investigation, and synthesis
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- 3dmem Bench EvalEvaluates an embodied 3D agent's ability to manage long-term spatial-temporal memory and execute complex, multi-room tasks. It probes the model's capacity for in-domain generalization, in-the-wild robustness, and long-horizon reasoning across navigation, question answering, and scene captioning. Use when the user wants to benchmark on 3DMem-Bench, or asks about evaluating this task. Reports success rate (SR).Votes: 0GitHub stars: 3
- 3d Vqa EvalEvaluates a model's ability to answer natural language questions about 3D indoor scenes using only multi-view RGB images. It probes spatial reasoning, semantic understanding, and zero-shot generalization across different embodied agent scenarios. Use when the user wants to benchmark on ScanQA, SQA3D, MSR3D, or asks about evaluating this task. Reports EM@1.Votes: 0GitHub stars: 3
- 3d Vln EvalEvaluates a model's ability to navigate 3D environments based on natural language instructions. It measures path efficiency, success in reaching targets, and robustness to scale calibration and data distribution shifts. Use when the user wants to benchmark on R2R, NaVILA, SceneVerse++ VLN, or asks about evaluating this task. Reports SR.Votes: 0GitHub stars: 3
- 3d Visual Grounding EvalEvaluates a model's ability to localize a specific 3D object within a scene based on a natural language description. It tests multimodal fusion of 3D point clouds, synthetic 2D views, and language to perform object classification and referring. Use when the user wants to benchmark on Nr3D, Sr3D, ScanRefer, or asks about evaluating this task. Reports referring accuracy.Votes: 0GitHub stars: 3
- 3d Spatial Vqa EvalTests a model's capacity for 3D spatial reasoning and scene understanding by answering questions about object counts, distances, directions, and room sizes. It evaluates how well foundation models can leverage automatically generated scene graphs and point cloud data for grounded visual question answering. Use when the user wants to benchmark on SceneVerse++ VQA, or asks about evaluating this task. Reports MCA Accuracy.Votes: 0GitHub stars: 3
- 3d Spatial Reasoning EvalEvaluates a model's ability to perform 3D visual grounding and situated question answering by reasoning over object coordinates and spatial relations in 3D scenes. It probes whether the model can accurately locate objects based on natural language instructions and answer spatial questions about scene layouts without linguistic interference. Use when the user wants to benchmark on ScanRefer, Multi3DRef, SQA3D, or asks about evaluating this task. Reports accuracy.Votes: 0GitHub stars: 3
- 3d Shape Retrieval EvalEvaluates algorithms for retrieving geometrically and topologically similar 3D shapes from a database given a query shape. Probes pose invariance, shape descriptor robustness, and retrieval ranking accuracy. Use when the user wants to benchmark on NIST shape benchmark, or asks about evaluating this task. Reports precision-recall.Votes: 0GitHub stars: 3
- 3d Semantic Segmentation EvalThis benchmark evaluates a model's ability to perform 3D semantic segmentation on indoor scenes. It probes the model's capacity to assign per-point semantic labels to 3D point clouds and assesses performance across head, common, and long-tail object categories. Use when the user wants to benchmark on ScanNet/ScanNet200, or asks about evaluating this task. Reports mIoU.Votes: 0GitHub stars: 3
- 3d Segmentation EvalEvaluates a unified transformer-based model's ability to perform instance and semantic segmentation on 3D point clouds derived from raw RGB-D sensor data. It probes cross-modal feature fusion between 2D images and 3D coordinates, and tests robustness to real-world sensor noise and misalignments compared to mesh-sampled inputs. Use when the user wants to benchmark on ScanNet, ScanNet200, or asks about evaluating this task. Reports mAP, mIoU.Votes: 0GitHub stars: 3
- 3d Scene Understanding EvalEvaluates a 3D vision-language model's ability to perform visual grounding, dense captioning, and situated question answering on indoor RGB-D scenes. It probes the model's capacity for precise object referencing, spatial reasoning, and open-ended language generation conditioned on 3D scene context. Use when the user wants to benchmark on ScanRefer, Multi3DRefer, Scan2Cap, ScanQA, SQA3D, or asks about evaluating this task. Reports Acc@0.5.Votes: 0GitHub stars: 3
- 3d Pose Estimation Manifold EvalEvaluates a model's ability to estimate 3D joint poses of articulated objects (mice, fish, human hands) from depth images. The benchmark probes continuous structured prediction on Lie group manifolds, requiring the model to output kinematic chain or tree configurations that align with ground-truth skeletal models. Use when the user wants to benchmark on Mouse, Fish, Human hand, or asks about evaluating this task. Reports average joint error.Votes: 0GitHub stars: 3
- 3d Obj Det Seg EvalEvaluates a model's ability to detect and segment 3D objects in indoor scenes using point cloud inputs. It probes spatial reasoning and instance-level understanding by measuring how well the model generalizes from synthetic internet-scale data to real-world scanned environments. Use when the user wants to benchmark on ScanNet, SceneVerse++, or asks about evaluating this task. Reports AP.Votes: 0GitHub stars: 3
- 3d Noc Power Thermal Reliability EvalEvaluates a simulation platform for predicting power consumption, thermal distribution, and reliability (MTTF) of 3D Networks-on-Chip under synthetic and application workloads. It compares TSV-based 3D-NoC designs against monolithic and 2D-IC alternatives, and assesses the impact of different floorplans and cooling strategies on thermal stress and failure rates. Use when the user wants to benchmark on PARSEC benchmark suite, Synthetic benchmarks (Matrix, HotSpot, Uniform, Transpose), or asks ...Votes: 0GitHub stars: 3
- 3d Multimodal EvalEvaluates a 3D large multimodal model's ability to understand spatial scenes and generate accurate text responses. It probes free-form question answering about 3D environments and object-centric dense captioning grounded in 3D coordinates. Use when the user wants to benchmark on ScanQA, SQA3D, ScanRefer, Nr3D, or asks about evaluating this task. Reports CiDEr.Votes: 0GitHub stars: 3
- 3d Mir EvalProbes the ability of medical imaging models to retrieve relevant 3D CT volumes based on lesion characteristics. It evaluates retrieval accuracy for binary lesion presence (flag) and morphological size categories (group) across four anatomical regions. Use when the user wants to benchmark on 3D-MIR, or asks about evaluating this task. Reports Average Precision (AP).Votes: 0GitHub stars: 3
- 3d Medical Seg EvalEvaluates the segmentation performance of various 3D medical image architectures across multiple public datasets. It probes whether newer architectures genuinely outperform established U-Net baselines when trained under standardized, hardware-scaled conditions without external advantages like ensembling or pretraining. Use when the user wants to benchmark on BTCV, ACDC, LiTS, BraTS, KiTS, AMOS, or asks about evaluating this task. Reports DSC score [%].Votes: 0GitHub stars: 3
- 3d Llm Benchmark EvalEvaluates whether Vision-Language Models (VLMs) and 3D LLMs genuinely understand 3D spatial reasoning or merely exploit 2D visual priors by rendering point clouds into images. It probes capabilities like object captioning, scene question-answering, and situation understanding across single-view, multi-view, and oracle-viewpoint settings. Use when the user wants to benchmark on 3D MM-Vet, ObjaverseXL-LVIS Caption, ScanQA, SQA3D, or asks about evaluating this task. Reports LLM-eval, EM.Votes: 0GitHub stars: 3
- 3d Ids EvalEvaluates network intrusion detection systems on identifying malicious traffic flows in IoT and general network environments. It probes the model's ability to handle severe class imbalance, dynamic graph topologies, and both known and unknown attack patterns using binary and multi-class classification tasks. Use when the user wants to benchmark on CIC-ToN-IoT, CIC-BoT-IoT, EdgeIIoT, NF-UNSW-NB15-v2, NF-CSE-CIC-IDS2018-v2, or asks about evaluating this task. Reports F1-score.Votes: 0GitHub stars: 3
- 3d Face Recon EvalEvaluates the accuracy and realism of 3D face reconstruction and generation from single 2D images. Probes shape reconstruction fidelity against ground truth meshes, texture identity preservation across novel poses, and the diversity of synthesized 3D faces. Use when the user wants to benchmark on NoW Benchmark, REALY 3D Benchmark, or asks about evaluating this task. Reports Per-vertex error (mm).Votes: 0GitHub stars: 3
- 3d Affordance Net EvalEvaluates 3D point cloud networks on visual object affordance understanding. It probes the model's ability to predict point-wise probabilistic scores for 18 affordance classes given full, partial, or rotated 3D shapes. Use when the user wants to benchmark on 3D AffordanceNet, or asks about evaluating this task. Reports mAP.Votes: 0GitHub stars: 3
- 360roam EvalEvaluates the capability of neural radiance field models to perform real-time, high-fidelity novel view synthesis on large-scale indoor scenes using 360° panoramic imagery. It probes the trade-off between rendering quality, computational efficiency, and geometric awareness in complex, unbounded indoor environments. Use when the user wants to benchmark on 360Roam Dataset, or asks about evaluating this task. Reports PSNR.Votes: 0GitHub stars: 3
- 2m Belebele EvalMultilingual reading comprehension across text and speech modalities. It probes a model's ability to understand spoken or written passages in 39 languages and answer multiple-choice questions based on them. Use when the user wants to benchmark on 2M-Belebele, or asks about evaluating this task. Reports accuracy.Votes: 0GitHub stars: 3
- Ml Paper WritingWrite publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.Votes: 0GitHub stars: 4
- Hugging Face Paper PublisherPublish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.Votes: 0GitHub stars: 4