├── .github └── workflows │ └── update_readme.yml └── README.md /.github/workflows/update_readme.yml: -------------------------------------------------------------------------------- 1 | name: Update README on New Issues 2 | 3 | on: 4 | schedule: 5 | # Run every Thursday at 00:00 UTC 6 | - cron: '0 0 * * 4' 7 | issues: 8 | types: [opened] 9 | workflow_dispatch: # Allow manual trigger 10 | 11 | jobs: 12 | update-readme: 13 | runs-on: ubuntu-latest 14 | permissions: 15 | contents: write 16 | issues: read 17 | 18 | steps: 19 | - name: Checkout repository 20 | uses: actions/checkout@v4 21 | with: 22 | fetch-depth: 0 23 | 24 | - name: Setup Python 25 | uses: actions/setup-python@v4 26 | with: 27 | python-version: '3.x' 28 | 29 | - name: Check for new issues and update README 30 | env: 31 | GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} 32 | run: | 33 | python - <<'EOF' 34 | import os 35 | import re 36 | import json 37 | import subprocess 38 | from datetime import datetime, timedelta 39 | 40 | # GitHub API setup 41 | github_token = os.environ['GITHUB_TOKEN'] 42 | repo = os.environ['GITHUB_REPOSITORY'] 43 | 44 | # Function to get issues from the last week 45 | def get_recent_issues(): 46 | # Check if triggered by issue event 47 | event_name = os.environ.get('GITHUB_EVENT_NAME') 48 | 49 | if event_name == 'issues': 50 | # Get the issue that triggered this workflow 51 | with open(os.environ['GITHUB_EVENT_PATH'], 'r') as f: 52 | event_data = json.load(f) 53 | issue = event_data.get('issue', {}) 54 | if issue: 55 | return [issue] 56 | else: 57 | # For scheduled runs, get issues from the last week 58 | one_week_ago = (datetime.now() - timedelta(days=7)).isoformat() 59 | cmd = f'''curl -s -H "Authorization: token {github_token}" \ 60 | "https://api.github.com/repos/{repo}/issues?state=all&since={one_week_ago}&sort=created&direction=desc"''' 61 | result = subprocess.run(cmd, shell=True, capture_output=True, text=True) 62 | issues = json.loads(result.stdout) 63 | 64 | # Filter for issues created in the last week 65 | recent_issues = [] 66 | for issue in issues: 67 | created_at = datetime.strptime(issue['created_at'], '%Y-%m-%dT%H:%M:%SZ') 68 | if created_at > datetime.now() - timedelta(days=7): 69 | recent_issues.append(issue) 70 | return recent_issues 71 | 72 | return [] 73 | 74 | # Function to parse issue title 75 | def parse_issue_title(title): 76 | # Expected format: "2025.08.27 - #48 - WALL-OSS, ORB-SLAM-Python, Robix, ..." 77 | # More strict pattern matching to ensure exact format 78 | pattern = r'^(\d{4}\.\d{2}\.\d{2})\s*-\s*#(\d+)\s*-\s*(.+)$' 79 | match = re.match(pattern, title) 80 | 81 | if match: 82 | date_str = match.group(1) 83 | issue_num = match.group(2) 84 | topics_str = match.group(3).strip() 85 | 86 | # Keep date format as is (YYYY.MM.DD) 87 | formatted_date = date_str 88 | 89 | # Clean up topics - preserve the comma-separated format 90 | topics = ', '.join([t.strip() for t in topics_str.split(',')]) 91 | 92 | return formatted_date, topics, issue_num 93 | return None, None, None 94 | 95 | # Function to update README 96 | def update_readme(new_entries): 97 | if not new_entries: 98 | print("No new issues to add to README") 99 | return False 100 | 101 | # Read current README 102 | with open('README.md', 'r') as f: 103 | content = f.read() 104 | 105 | # Find the table - match table with proper row endings 106 | table_pattern = r'(\|Date\|Topics\|Link\|Video\|\n\|[-]+\|[-]+\|[-]+\|[-]+\|(?:\n\|[^\n]+\|)*)' 107 | match = re.search(table_pattern, content) 108 | 109 | if not match: 110 | print("Could not find the table in README.md") 111 | return False 112 | 113 | table_content = match.group(1) 114 | 115 | # Parse existing entries to check for duplicates and maintain order 116 | existing_entries = [] 117 | lines = table_content.strip().split('\n') 118 | for line in lines[2:]: # Skip header lines 119 | if line.strip() and line.startswith('|'): 120 | existing_entries.append(line) 121 | 122 | # Check for duplicates and add new entries 123 | added_count = 0 124 | new_rows = [] 125 | for entry in new_entries: 126 | # Check if this issue is already in the table 127 | issue_link = f"[meeting log]({entry['link']})" 128 | if not any(issue_link in row for row in existing_entries): 129 | new_row = f"|{entry['date']}| {entry['topics']} |{issue_link}| |" 130 | new_rows.append(new_row) 131 | added_count += 1 132 | print(f"Added new entry: {entry['date']} - {entry['topics']}") 133 | 134 | if added_count == 0: 135 | print("All issues already exist in the table") 136 | return False 137 | 138 | # Combine all entries and sort by date 139 | all_rows = existing_entries + new_rows 140 | 141 | # Sort entries by date (assuming YYYY.MM.DD format) 142 | def get_date_key(row): 143 | date_match = re.search(r'\|(\d{4}\.\d{2}\.\d{2})\|', row) 144 | if date_match: 145 | return date_match.group(1) 146 | return '9999.99.99' # Put malformed rows at the end 147 | 148 | all_rows.sort(key=get_date_key) 149 | 150 | # Rebuild the table with proper formatting 151 | header = "|Date|Topics|Link|Video|\n|------|---|---|---|" 152 | sorted_rows = '\n'.join(all_rows) 153 | new_table = f"{header}\n{sorted_rows}" 154 | 155 | # Replace old table with new table 156 | new_content = content.replace(table_content, new_table) 157 | 158 | # Write updated README 159 | with open('README.md', 'w') as f: 160 | f.write(new_content) 161 | 162 | print(f"Successfully added {added_count} new entries to README.md") 163 | return True 164 | 165 | # Main execution 166 | recent_issues = get_recent_issues() 167 | 168 | if not recent_issues: 169 | print("No new issues found") 170 | exit(0) 171 | 172 | new_entries = [] 173 | for issue in recent_issues: 174 | # Skip pull requests 175 | if 'pull_request' in issue: 176 | continue 177 | 178 | date, topics, issue_num = parse_issue_title(issue['title']) 179 | if date and topics: 180 | new_entries.append({ 181 | 'date': date, 182 | 'topics': topics, 183 | 'link': issue['html_url'] 184 | }) 185 | print(f"Processing issue #{issue_num}: {date} - {topics}") 186 | else: 187 | print(f"Issue '{issue['title']}' does not match expected format, skipping") 188 | 189 | if new_entries: 190 | if update_readme(new_entries): 191 | print("README.md has been updated") 192 | else: 193 | print("No updates needed for README.md") 194 | else: 195 | print("No valid issues to process") 196 | EOF 197 | 198 | - name: Commit and push changes 199 | run: | 200 | git config --local user.email "action@github.com" 201 | git config --local user.name "GitHub Action" 202 | 203 | # Check if there are changes 204 | if git diff --quiet; then 205 | echo "No changes to commit" 206 | else 207 | git add README.md 208 | git commit -m "Update README.md with new issue information" 209 | git push 210 | echo "Changes pushed to repository" 211 | fi 212 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # WeeklySpatialAI 🥳 2 | 3 | `Weekly Spatial AI`는 매주 [Spatial AI KR](https://www.facebook.com/groups/spatialaikr/) 커뮤니티 멤버들이 온라인 모임을 통해 최신 Spatial AI 뉴스 및 자료를 공유하는 모임입니다. 4 | 5 | `Weekly Spatial AI` is a weekly online meetup amongst the members of the [Spatial AI KR](https://www.facebook.com/groups/spatialaikr/) community to share the latest news on Spatial AI. 6 | 7 | ## Vision 8 | 9 | Spatial AI 분야의 현업자, 대학원생, 교수님들간의 정보교환 -> 최신 논문, 업계 현황, 신기술/신제품, 개발 노하우, 채용 공고, 유용한 테크 블로그 등... 10 | 11 | Information exchange between experts in Spatial AI field from industry to academia -> latest papers, industry news, tips for development, latest technologies/products, job postings, useful tech blogs... 12 | 13 | ## Meeting history 14 | 15 | 미팅 영상은 [YouTube 채널](https://www.youtube.com/@slam_slam_/)에, 미팅 로그는 [Issue 페이지](https://github.com/changh95/WeeklySpatialAI/issues)에 남깁니다. 16 | 17 | We post our meeting videos on our [YouTube Channel](https://www.youtube.com/@slam_slam_/), and our meeting logs on the [issue page](https://github.com/changh95/WeeklySpatialAI/issues). 18 | 19 | 아래 이미지를 클릭하시면 재생목록으로 이동합니다. 20 | 21 | Click the image below, and you'll be directed to the YouTube playlist. 22 | 23 | 24 | image 25 | 26 | 27 | |Date|Topics|Link|Video| 28 | |------|---|---|---| 29 | |2024.07.24| FutureMapping, GLIM, DeepSLAM, Co-RAL, SOLiD, ETPNav, GeFF |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/1)| [YouTube](https://youtu.be/3QUdewSpPr8?si=qKQ9an-odCd8EvoU)| 30 | |2024.07.31| MASt3R, GLOMAP, ACE 0, VGGSfM, SAM v2, fVDB, Clio, MeshAnything, RT-2 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/4)| [YouTube](https://youtu.be/dH_LWuV0o4M?si=s6zG8TGcdM1PFQCI)| 31 | |2024.08.07| Figure 02, InstantSplat, BADROBOT, COIN-LIO, Universal Manipulation Interface |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/5)| [YouTube](https://youtu.be/tJ5_WKULmVQ?si=Bx6ddkifa_KQKWKi)| 32 | |2024.08.14| DeepMind table tennis robot, FLUX, CppCon, MoAI, CoLLaVO, Hydra-MDP, NPU overview |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/6)| [YouTube](https://youtu.be/MDvD_JEv9SY?si=wCYA2n5kpxQHx6Gn)| 33 | |2024.08.21| Tenstorrent NPU, ROS LLM agent, Industrial 3D scanner review, Skydio X10 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/7)| [YouTube](https://youtu.be/Pi-DYBK3bxs?si=b8tK8BkpSvUXir2A)| 34 | |2024.08.28| Sapiens, GaussianOcc, FAST-LIVO2, SOLiD-ALOAM, Berkeley Humanoid, NavGPT-2 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/8)| [YouTube](https://youtu.be/gaRviiuPdGI?si=fLppi_C_v_ouU-Ix)| 35 | |2024.09.11| GenWarp, ReconX, OmniRe, FIT3D, NVIDIA GPU Overview |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/9)| [YouTube](https://youtu.be/Rr45MAeHJz0?si=GyfyW_m92NpRUynt)| 36 | |2024.09.25| World models (Wayve, 1X, World Labs), MaskBEV, RockChip micro-NPU, M2-Mapping |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/10)| [YouTube](https://youtu.be/bX2iCM1sJ1g?si=yx2Su5E3r_9sTaoh)| 37 | |2024.10.01| MASt3R-SfM, Hyperion, latentSplat, RL meets VO, Aria dataset, NVIDIA GPU overview part 2 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/11)| [YouTube](https://youtu.be/ZTtJc_nhQro?si=FoWj25RuUcPGzqDn)| 38 | |2024.10.09| MonST3R, Depth Pro, EVER, KISS-Matcher, Nano-PGO, ST-P3 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/12)| [YouTube](https://youtu.be/6XjZGPOmF40?si=h3WpdM2FBMWaVbos)| 39 | |2024.10.15| CLIP-Clique, FoundPose, Tesla CyberCab/Robovan, MEVIUS, WildFusion, 𝛼LiDAR |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/13)| [YouTube](https://youtu.be/RbpVLH6ckwc?si=0M6muWJn14dFKyll)||2024.10.23| PROSAC, Efficient descriptors, PhD/professor hiring, UniTR, DSVT, BEVFusion, MaskBEV |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/14)| [YouTube](https://youtu.be/pkiOuSHlIWw?si=cmMDz0_IboiMHZRn)| 40 | |2024.10.30| Vision-Language Model (VLM), Large Spatial Model, PLGS, Niantic Scaniverse |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/15)| [YouTube](https://youtu.be/8VwFxTfgpxk?si=i38h8Nh52_0ZtyFm)| 41 | |2024.11.06| MAC-VO, KISS-Matcher, PyTorch Mobile, Metal API, Neural fields in robotics, Visual SLAM roadmap |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/16)| [YouTube](https://youtu.be/x5c6wS6ID2M?si=LulbiZsAyNrQ9AlH)| 42 | |2024.11.13| CoVLA, Accelerated image processing for VSLAM, 2024 3D object & view generation overview |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/17)| [YouTube](https://youtu.be/1C76hyMirmQ?si=he4Ke1cLe9VXLGTM)| 43 | |2024.11.20| SLAM Handbook, Oxford Spires dataset, llava-o1, llama-mesh, Figure-02 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/18)| [YouTube](https://youtu.be/76HkebJ9aSc?si=danO1n0Wi5tKatQE)| 44 | |2024.11.27| MAGiC-SLAM, DROID-Splat, Splat-AD, OVO-SLAM, YOLO-cpp, ALIKED-cpp |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/19)| [YouTube](https://youtu.be/lGrnMPWbjeE) | 45 | |2024.12.04| L3DG, IG-SLAM, ULSR-GS, ROVER, World Labs demo, MVD2, FastSR-NeRF, Zero-to-Hero |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/20)| [YouTube](https://youtu.be/3zzVfLuvUNU) | 46 | |2024.12.11| RL tutorial, NaVILA, GS-LIVM, Bonsai, MEVIUS, DiTer++, MOANA dataset, MAN TruckScenes |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/21)| [YouTube](https://youtu.be/Y0UjnuuzlQY) | 47 | |2024.12.18| MASt3R-SLAM, DiTER++, CAT4D, pixelSplat, LiveScene, Talking to DINO, MV-DUSt3R, Diorama, MegaSaM, NaVILA |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/22)| [YouTube](https://youtu.be/F3o9R2UdG6Q) | 48 | |2025.01.08| Gaussian Belief Propgation paper, NVIDIA 50xx GPU, Open X-embodiment, DROID, Genesis, Robogen, Foundation model survey |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/23)| [YouTube](https://youtu.be/hjKomzqTX4o) | 49 | |2025.01.22| NVIDIA NIM, Cosmos, new Hesai/Robosense LiDAR, MatchAnything, HF smolagents, DeepSeek-R1 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/24)| [YouTube](https://youtu.be/m9aV90PEyB0) | 50 | |2025.02.05| Pi0, AnyTeleop, Paper list for Object SLAM / Semantic SLAM / SLAM with scene graph representation |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/25)| [YouTube](https://youtu.be/wjucr9R48OQ) | 51 | |2025.02.19| Latent radiance field, robust autonomy from self-play, COLMAP-free 3DGS, LightGaussian, Compact 3DGS |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/26)| [YouTube](https://www.youtube.com/watch?v=YakL5eFvARY)| 52 | |2025.02.26| MASt3r-SLAM, CUT3R, PointMamba, Human demonstration data, 3D Gaussian Splatting overview |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/27)| [YouTube](https://www.youtube.com/watch?v=YFq3yMsERWI)| 53 | |2025.03.05| SfM survey, Embodied AI simulator survey, PINGS, ESAM, Hier-SLAM++, S-Graphs 2.0, Fast3r |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/28)| [YouTube](https://youtu.be/TJMmPrAIC84?si=kP9frnmZ4pLKYnKc) | 54 | |2025.03.12| CURB-OSG, GigaSLAM, QLIO, Hennessy & Patterson, 딥러닝 & SLAM 강의 추천 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/29)| [YouTube](https://www.youtube.com/watch?v=2F3voDCiF2k)| 55 | |2025.03.19| KISS-SLAM, NVIDIA Spark, RoboSense E1R review, VGGT, RelationField, CUDA study |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/30)| [YouTube](https://www.youtube.com/watch?v=lYpOOG3l7u4)| 56 | |2025.03.26| MS Cooperative vector, Map-free visual localization, CoCreatAR, HOMIE, low-cost manipulation |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/31)| [YouTube](https://www.youtube.com/watch?v=J00xVp7C4FA)| 57 | |2025.04.09| Figure AI 투어, Tesla 투어, Llama 4, LLM + JSON, GIL in Python |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/32)| [YouTube](https://www.youtube.com/watch?v=rwQATGq2Z4k)| 58 | |2025.04.16| Tenstorrent Blackhole, SKiD-SLAM, 4D radar review |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/33)| [YouTube](https://www.youtube.com/watch?v=GSvK99HHt_4)| 59 | |2025.04.23| EDGS, RoMa |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/34)| [YouTube](https://www.youtube.com/watch?v=RJi4yTu_PcU)| 60 | |2025.04.30| Qwen3, LiteGS, GenZ-ICP improved, MambaGlue, OpenLiDARMap |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/35)| [YouTube](https://www.youtube.com/watch?v=TgeMjnDHtfI)| 61 | |2025.05.07| NVIDIA/AMD/Google/Furiosa GPU NPU TPU 리뷰, Differentiable rendering 리뷰 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/36)| [YouTube](https://www.youtube.com/watch?v=Z1Q3t-Mgn5U)| 62 | |2025.05.15| SceneScript, GLIM-CPU, Google's 3D generation, PyRoki, VINS-Multi, ForceMimic |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/37)| [YouTube](https://www.youtube.com/watch?v=ayQXDSy2j5k)| 63 | |2025.05.28| VGGT-SLAM, ASHiTA, 3DGUT, CLAMP, XLeRobot |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/38)| [YouTube](https://www.youtube.com/watch?v=DLNzV-Z42Lc)| 64 | |2025.06.04| E3D-Bench, On-the-fly-reconstruction 3D Gaussian Splatting |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/39)| [YouTube](https://www.youtube.com/watch?v=pMSNRaNFyb8)| 65 | |2025.06.11| FreeTimeGS, PartCrafter, SuperRANSAC, 4DGT, STORM, LocoTouch, SuperLoc |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/40)| [YouTube](https://www.youtube.com/watch?v=-JGBxXqHqmE)| 66 | |2025.06.18| UFM, Pow3r, OpenGS-SLAM, DGN |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/41)| [YouTube](https://www.youtube.com/watch?v=jViCwEvJ8UI)| 67 | |2025.06.25| 3D-GRUT, On-the-Fly-NVS, XFeat, VLMgineer, IMLE Policy |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/42)| [YouTube](https://www.youtube.com/watch?v=mbA7FiJYwaI)| 68 | |2025.07.09| PanoGS, SpatialTrackerV2, LiteReality, WildGS-SLAM, HI-SLAM2, MASt3r-SLAM, MAGiC-SLAM, MNE-SLAM |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/43)| [YouTube](https://www.youtube.com/watch?v=MYATKJHADtg)| 69 | |2025.07.16| PRoPE, VGGT-Long, Pangu Ultra MoE, GPU/NPU Simulator, WorldVLA |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/44)| [YouTube](https://youtu.be/l48QRQioBAE?si=C_frqOBVEDUd3miA) | 70 | |2025.07.23| Claude code, Qwen3-Coder, Gemma3n, EXAONE 4.0, RL math, OpenAI에서 일한 경험 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/45)| [YouTube](https://www.youtube.com/watch?v=HK7TQcJB2z0)| 71 | |2025.07.30| Feed-forward 3D recon survey, ThinkAct, ROMAN, UA-MPC, TurboClique |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/46)| [YouTube](https://youtu.be/LhLPtGk1PjA) | 72 | |2025.08.06| Google Genie3, OpenAI gpt-oss, Ollama Turbo, Anthropic Claude Opus-4.1 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/47)| [YouTube](https://youtu.be/zISMxNVb7dc) | 73 | |2025.08.20| Context as Memory, GameFactory, ReMEmbR, Anything 시리즈 리뷰, ECoT |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/48)| [YouTube](https://youtu.be/9nSInpXR0tY?si=NS86ZCjc-m3xEuMF) | 74 | |2025.08.27| Transformer-based SLAM, MineCraft ROS2 mod, Orin vs Thor benchmark, World Models in Autonomous Driving |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/49)| [YouTube](https://youtu.be/M2j4BzS7pDk?si=8kelMwQA7kLBNQvU) | 75 | |2025.09.10| WALL-OSS, ORB-SLAM-Python, Robix, TunedLens, Gemma Scope, Logit Prisms, Manim, TransformerLens, SAELens |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/50)| [YouTube](https://youtu.be/GKCrY7VUp-Y?si=SrSQw6YS-8KEd67k) | 76 | |2025.09.17| ViPE, Maps for Autonomous Driving survey, TeraSim-World |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/51)| [YouTube](https://youtu.be/PHTlXSLVlH4?si=DxutB6S6AA3tsGnM) | 77 | |2025.09.24| MapAnything, GMT, Any2Track, Behavior foundation model, EchoScene, SG Aligner |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/52)| [YouTube](https://youtu.be/4UmiSg4NgfI?si=ZtezSi3KFHEnKHdU) | 78 | |2025.10.15| OKVIS2-X, Open-YOLO 3D, CoT-VLA, π0.5, RND1, SuperDec |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/53) | [YouTube](https://youtu.be/1NcVS6CFOqw?si=TlxFmVd2VaYo0m-6) | 79 | |2025.10.22| SLAM 강의, WorldVLA, SceneDINO, VoT, InstantSfM, SAM3 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/54)| [YouTube](https://youtu.be/UL1hbEma9GE?si=-fL6QvaRjMYHBwwF) | 80 | |2025.10.29| Unitree 탐방기, From Masks to Worlds: A Hitchhiker's Guide to World Models |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/55)| [YouTube](https://youtu.be/ZfReAetf8xk?si=8XZm2wTrioNvmdA6) | 81 | |2025.11.05| GPU 26만장, Online-monocular-3DGS, ActiveSplat, Align3r |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/56)| | 82 | |2025.11.12| Vulkan shader, Human Characters to Humanoid, Egocentric-10K, NVIDIA AD dataset, LiteTracker |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/57)| | 83 | |2025.11.26| VLM review, SAM 3D, Nano Banana Pro, C++ rant |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/58)| | 84 | |2025.12.03| MASt3R-Fusion, EGG-Fusion, AMB3R, LEGS, D-NeRF, DreamerV3, ENACT, GigaBrain-0 |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/59)| | 85 | |2025.12.10| Alpamayo-R1, MobileVLA-R1, VLA-based Safe AI by Waymo |[meeting log](https://github.com/changh95/WeeklySpatialAI/issues/60)| | 86 | 87 | ## Our wonderful contributors 😃 88 | 89 | 90 | 91 | 92 | 93 | 94 | 95 | 96 | 97 | 98 | 99 | 100 | 101 | 102 |

Hyunggi Chang
:octocat:
Hyunwoo Joo
:octocat:
Juwon Kim
:octocat:
Jiyeon Lim
:octocat:
Chaeyoung Lee
:octocat:
Sunbin Kim
:octocat:
Minkyung Lee
:octocat:
103 | --------------------------------------------------------------------------------