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Cursor Agent edited this page Jul 2, 2026
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DeiT: Training data-efficient image transformers & distillation through attention —
vision,transformers,distillation— 2026-05-31 -
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows —
vision,transformers— 2026-05-31 -
π_0: A Vision-Language-Action Flow Model for General Robot Control —
vision,robotics— 2026-06-01 -
Segment Anything —
vision,instance-segmentation— 2026-06-02 -
DETRs Beat YOLOs on Real-time Object Detection —
vision,object-detection,transformers— 2026-06-03 -
FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects —
vision,6dof-pose-estimation— 2026-06-04 -
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis —
vision,neural-rendering— 2026-06-05 -
Masked Autoencoders Are Scalable Vision Learners —
masked-image-modeling,auto-encoders,self-supervised-learning,transformers,representation-learning— 2026-06-06 -
On the Spectral Bias of Neural Networks —
optimization,robustness,representation-learning,data-representation— 2026-06-08 -
RF-DETR: Neural Architecture Search for Real-Time Detection Transformers —
object-detection,instance-segmentation,neural-architecture-search,transformers— 2026-06-09 -
Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision —
3d-reconstruction,implicit-representations,neural-rendering,multi-view-stereo,depth-estimation— 2026-06-10 -
Deep Marching Cubes: Learning Explicit Surface Representations —
3d-reconstruction,data-representation,optimization— 2026-06-11 -
Occupancy Networks: Learning 3D Reconstruction in Function Space —
3d-reconstruction,implicit-representations,data-representation— 2026-06-12 -
Fast Inference from Transformers via Speculative Decoding —
speculative-decoding,transformers,language— 2026-06-13 -
Learning Transferable Visual Models From Natural Language Supervision —
vlm,contrastive-learning,zero-shot,representation-learning,open-vocabulary— 2026-06-14 -
YOLO26: Key Architectural Enhancements and Performance Benchmarking for Real-Time Object Detection —
object-detection,instance-segmentation,keypoint-detection,optimization,robotics— 2026-06-15 -
Occupancy Flow: 4D Reconstruction by Learning Particle Dynamics —
4d-reconstruction,implicit-representations,flow-maps,motion-estimation,temporal-coherence— 2026-06-16 -
SketchVLM: Vision language models can annotate images to explain thoughts and guide users —
vlm,visual-question-answering,grounding— 2026-06-17 -
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control —
robotics,vlm,transformers,language,grounding— 2026-06-18 -
LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels —
jepa,world-simulation,representation-learning,self-supervised-learning,robotics— 2026-06-19 -
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning —
transformers,optimization— 2026-06-22 -
FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision —
transformers,optimization,language— 2026-06-23 -
Emerging Properties in Self-Supervised Vision Transformers —
self-supervised-learning,transformers,representation-learning,distillation— 2026-06-24 -
Perception Encoder: The best visual embeddings are not at the output of the network —
contrastive-learning,representation-learning,vlm,distillation,object-detection— 2026-06-25 -
Neural Ordinary Differential Equations —
optimization,normalizing-flows,auto-encoders,representation-learning— 2026-06-26 -
SAM 2: Segment Anything in Images and Videos —
instance-segmentation,object-tracking,visual-tracking,transformers,temporal-coherence— 2026-06-30 -
SAM 3: Segment Anything with Concepts —
open-vocabulary,instance-segmentation,object-detection,object-tracking,semantic-segmentation— 2026-07-01 -
Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision —
3d-reconstruction,implicit-representations,neural-rendering,multi-view-stereo— 2026-07-02